Uncommon Descent Serving The Intelligent Design Community

On FSCO/I vs. Needles and Haystacks (as well as elephants in rooms)

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Sometimes, the very dismissiveness of hyperskeptical objections is their undoing, as in this case from TSZ:

Pesky EleP(T|H)ant

Over at Uncommon Descent KirosFocus repeats the same old bignum arguments as always. He seems to enjoy the ‘needle in a haystack’ metaphor, but I’d like to counter by asking how does he know he’s not searching for a needle in a needle stack? . . .

What had happened, is that on June 24th, I had posted a discussion here at UD on what Functionally Specific Complex Organisation and associated Information (FSCO/I) is about, including this summary infographic:

csi_defnInstead of addressing what this actually does, RTH of TSZ sought to strawmannise and rhetorically dismiss it by an allusion to the 2005 Dembski expression for Complex Specified Information, CSI:

χ = – log2[10^120 ·ϕS(T)·P(T|H)].

–> χ is “chi” and ϕ is “phi” (where, CSI exists if Chi > ~ 1)

. . . failing to understand — as did the sock-puppet Mathgrrrl [not to be confused with the Calculus prof who uses that improperly appropriated handle) — that by simply moving forward to the extraction of the information and threshold terms involved, this expression reduces as follows:

To simplify and build a more “practical” mathematical model, we note that information theory researchers Shannon and Hartley showed us how to measure information by changing probability into a log measure that allows pieces of information to add up naturally:

Ip = – log p, in bits if the base is 2. That is where the now familiar unit, the bit, comes from. Where we may observe from say — as just one of many examples of a standard result — Principles of Comm Systems, 2nd edn, Taub and Schilling (McGraw Hill, 1986), p. 512, Sect. 13.2:

Let us consider a communication system in which the allowable messages are m1, m2, . . ., with probabilities of occurrence p1, p2, . . . . Of course p1 + p2 + . . . = 1. Let the transmitter select message mk of probability pk; let us further assume that the receiver has correctly identified the message [[–> My nb: i.e. the a posteriori probability in my online discussion here is 1]. Then we shall say, by way of definition of the term information, that the system has communicated an amount of information Ik given by

I_k = (def) log_2  1/p_k   (13.2-1)

xxi: So, since 10^120 ~ 2^398, we may “boil down” the Dembski metric using some algebra — i.e. substituting and simplifying the three terms in order — as log(p*q*r) = log(p) + log(q ) + log(r) and log(1/p) = log (p):

Chi = – log2(2^398 * D2 * p), in bits,  and where also D2 = ϕS(T)
Chi = Ip – (398 + K2), where now: log2 (D2 ) = K
That is, chi is a metric of bits from a zone of interest, beyond a threshold of “sufficient complexity to not plausibly be the result of chance,”  (398 + K2).  So,
(a) since (398 + K2) tends to at most 500 bits on the gamut of our solar system [[our practical universe, for chemical interactions! ( . . . if you want , 1,000 bits would be a limit for the observable cosmos)] and
(b) as we can define and introduce a dummy variable for specificity, S, where
(c) S = 1 or 0 according as the observed configuration, E, is on objective analysis specific to a narrow and independently describable zone of interest, T:

Chi =  Ip*S – 500, in bits beyond a “complex enough” threshold

  • NB: If S = 0, this locks us at Chi = – 500; and, if Ip is less than 500 bits, Chi will be negative even if S is positive.
  • E.g.: a string of 501 coins tossed at random will have S = 0, but if the coins are arranged to spell out a message in English using the ASCII code [[notice independent specification of a narrow zone of possible configurations, T], Chi will — unsurprisingly — be positive.

explan_filter

  • S goes to 1 when we have objective grounds — to be explained case by case — to assign that value.
  • That is, we need to justify why we think the observed cases E come from a narrow zone of interest, T, that is independently describable, not just a list of members E1, E2, E3 . . . ; in short, we must have a reasonable criterion that allows us to build or recognise cases Ei from T, without resorting to an arbitrary list.
  • A string at random is a list with one member, but if we pick it as a password, it is now a zone with one member.  (Where also, a lottery, is a sort of inverse password game where we pay for the privilege; and where the complexity has to be carefully managed to make it winnable. )
  • An obvious example of such a zone T, is code symbol strings of a given length that work in a programme or communicate meaningful statements in a language based on its grammar, vocabulary etc. This paragraph is a case in point, which can be contrasted with typical random strings ( . . . 68gsdesnmyw . . . ) or repetitive ones ( . . . ftftftft . . . ); where we can also see by this case how such a case can enfold random and repetitive sub-strings.
  • Arguably — and of course this is hotly disputed — DNA protein and regulatory codes are another. Design theorists argue that the only observed adequate cause for such is a process of intelligently directed configuration, i.e. of  design, so we are justified in taking such a case as a reliable sign of such a cause having been at work. (Thus, the sign then counts as evidence pointing to a perhaps otherwise unknown designer having been at work.)
  • So also, to overthrow the design inference, a valid counter example would be needed, a case where blind mechanical necessity and/or blind chance produces such functionally specific, complex information. (Points xiv – xvi above outline why that will be hard indeed to come up with. There are literally billions of cases where FSCI is observed to come from design.)

xxii: So, we have some reason to suggest that if something, E, is based on specific information describable in a way that does not just quote E and requires at least 500 specific bits to store the specific information, then the most reasonable explanation for the cause of E is that it was designed. The metric may be directly applied to biological cases:

Using Durston’s Fits values — functionally specific bits — from his Table 1, to quantify I, so also  accepting functionality on specific sequences as showing specificity giving S = 1, we may apply the simplified Chi_500 metric of bits beyond the threshold:
RecA: 242 AA, 832 fits, Chi: 332 bits beyond
SecY: 342 AA, 688 fits, Chi: 188 bits beyond
Corona S2: 445 AA, 1285 fits, Chi: 785 bits beyond

Where, of course, there are many well known ways to obtain the information content of an entity, which automatically addresses the “how do you evaluate p(T|H)” issue. (As has been repeatedly pointed out, just insistently ignored in the rhetorical intent to seize upon a dismissive talking point.)

There is no elephant in the room.

Apart from . . . the usual one design objectors generally refuse to address, selective hyperskepticism.

But also, RTH imagines there is a whole field of needles, refusing to accept that many relevant complex entities are critically dependent on having the right parts, correctly arranged, coupled and organised in order to function.

That is, there are indeed empirically and analytically well founded narrow zones of functional configs in the space of possible configs. By far and away most of the ways in which the parts of a watch may be arranged — even leaving off the ever so many more ways they can be scattered across a planet or solar system– will not work.

The reality of narrow and recognisable zones T in large spaces W beyond the blind sampling capacity — that’s yet another concern — of a solar system of 10^57 atoms or an observed cosmos of 10^80 or so atoms and 10^17 s or so duration, is patent. (And if RTH wishes to dismiss this, let him show us observed cases of life spontaneously organising itself out of reasonable components, say soup cans. Or, of watches created by shaking parts in drums, or of recognisable English text strings of at least 72 characters being created through random text generation . . . which last is a simple case that is WLOG, as the infographic points out. As, 3D functional arrangements can be reduced to code strings, per AutoCAD etc.)

Finally, when the material issue is sampling, we do not need to generate grand probability calculations.

The proverbial needle in the haystack
The proverbial needle in the haystack

For, once we are reasonably confident that we are looking at deeply isolated zones in a field of possibilities, it is simple to show that unless a “search” is so “biased” as to be decidedly not random and decidedly not blind, only a blind sample on a scope sufficient to make it reasonably likely to catch zones T in the field W would be a plausible blind chance + mechanical necessity causal account.

But, 500 – 1,000 bits (a rather conservative threshold relative to what we see in just the genomes of life forms) of FSCO/I is (as the infographic shows) far more than enough to demolish that hope. For 500 bits, one can see that to give every one of the 10^57 atoms of our solar system a tray of 500 H/T coins tossed and inspected every 10^-14 s — a fast ionic reaction rate — would sample as one straw to a cubical haystack 1,000 LY across, about as thick as our galaxy’s central bulge. If such a haystack were superposed on our galactic neighbourhood and we were to take a blind, reasonably random one-straw sized sample it would with maximum likelihood be straw.

As in, empirically impossible, or if you insist, all but impossible.

 

It seems that objectors to design inferences on FSCO/I have been reduced to clutching at straws. END

Comments
D-J: Info carrying capacity maxes out at a flat distribution, and anything other will be somewhat different and less. But prevalence of A/G/C/T or U and the 20 proteins in general and for specific families has long been studied as can be found in Yockey's studies. The Durston metrics of H reflect this, which comes out in SUM pi log pi metrics. What happens is that AFTER going to H-values on functional vs ground vs null states -- family, general distribution, flat distribution, using those for I and addressing the 500 bit threshold, of Durston's 15 families, I gave three results, chosen to illustrate the point:
RecA: 242 AA, 832 fits, Chi: 332 bits beyond SecY: 342 AA, 688 fits, Chi: 188 bits beyond Corona S2: 445 AA, 1285 fits, Chi: 785 bits beyond
Immaterial, even for individual proteins. And in aggregate, the genomes are of order 100,000 - 1 mn kbases at the low end. Toss 98% as junk and treat the 2,000 bases for 100 k bases as one bit per base not two, we are still in "designed" territory. That's before addressing the associated organisation of machinery which must be going concern in a living cell for DNA to work. That raises issues of FSCO/I beyond protein codes in the DNA. A more realistic number for a low end independent cell based life form is 300 kbases. In short, no material difference, even giving concessions that should not be given just so. Remember, at OOL, the chemistry and thermodynamics of chaining do not program which base follows which, and that if it did, info capacity would be zero. The biochemical predestination thesis Kenyon et al put forth in the 60's, on proteins did not survive examination of chaining patterns. (Indeed that is part of how Kenyon, in writing the foreword to TMLO, c 1984, repudiated his thesis.) And more . . . KFkairosfocus
October 25, 2014
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kf noted
in info contexts reduce info capacity...
Agreed; therefore any 'bit-counting' method will be inaccurate
...[but in our case not materially]
Aye, there's the rub! What is the basis for this claim? How have you quantified the magnitude of the error? Please be precise.DNA_Jock
October 25, 2014
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Still no real-world CSI calculations from any of the ID crowd. Oh well.Thorton
October 25, 2014
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D-J: I made no such claim, please do not pigeon-hole and strawmannise me. I simply pointed out the significance and utility of the principle (which is undeniable regardless of debates made, note dice, card and coin cases, other assignments modify this . . . and in info contexts reduce info capacity [but in our case not materially]), and that there is a more complex SUM of pi log pi approach used with Shannon's H metric and other cases. I take as much more basic the approach of string length of y/n q's to specify state in a high contingency context. Beyond, I pointed out that the Durston et al approach, building on the H metric, uses the actual history of life as recorded in protein family variability, is in effect a real world Monte Carlo search which can characterise realistic distribution. Is it not 3.8 - 4.2 Bn y on the usual timeline for sampling, and c 600 MY for extant complex forms of esp animals. So, there is a practical, real world Monte Carlo sim run pattern that allows H, avg info per symbol or relevant message bloc, to be deduced. We have reasonable access to info metrics, by simple 20 states per AA, or by H-metric assessed off real life variability in protein families. So, the silly schoolyard taunts on elephants in rooms collapse. Protein chains are info bearing and are functionally specific, in aggregate are well beyond the sort of thresholds that make blind chance and necessity utterly implausible, and with the associated phenomena of codes, algorithms and execution machinery, strongly point to design of the cell based life form. KFkairosfocus
October 25, 2014
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The anti-ID mob can try to make fun of CSI and all of its variants but they sure as hell cannot provide any methodology that shows unguided processes can account for Crick's defined biological information that is found in all living organisms. IOW the anti-ID mob is full of cowards.Joe
October 25, 2014
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DNA_jock- the problem with using probabilities is that evos cannot provide any. Just allowing probabilities is giving evos more than they deserve.Joe
October 25, 2014
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As the bystander wrote:
Iam curious to know what other probability distribution would you use if there is no way of finding the probability of every possible state
I agree - which makes calculating p(T|H) problematic. I think it is even worse: you cannot find the probability of any state, which makes calculating p(T|H) impossible. But I could be wrong...DNA_Jock
October 25, 2014
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So your answer is "All prior probabilities are equal, by the principle of indifference". Excellent. That's specific, although rather difficult to justify. It does have the weight of tradition behind it, and I think I would make the same assumption myself. Next up: Once you have selected a value at one position, are the other states still all equiprobable? Or, to put it another way, are all the dimensions in your config space completely independent from all other dimensions?DNA_Jock
October 25, 2014
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FYI-FTR: https://uncommondescent.com/atheism/fyiftr-making-basic-sense-of-fscoi-functionally-specific-complex-organisation-and-associated-information/kairosfocus
October 25, 2014
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DD, I hear your point -- and I suspect, so does Management, but obviously factors we are not privy to were at work. KFkairosfocus
October 25, 2014
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D-J: I am not making any particular probability assignment beyond what is implicit in normal constructions of information. We could have a side debate on the Bernouilli-Laplace principle of indifference as the first point of debates about probabilities and go on to the entropy approach used by Shannon to get the SUM pi log pi value that gives avg info per symbol, and how this is connected to entropy of a macrostate as the average lack of info (think Y/N q chain length to specify microstate given lab observable parameters specifying macro state), etc, but that would be a grand detour liable to even more pretzel twisting. Simply follow up on how monte carlo sims run as a set allow characterisation of the stochastic behaviour of a system as an exercise in sampling. Then understand that there are logical possibilities that are too remote relative to dominant clusters that lead to the needle in haystack search challenge with limited resources. The comparative I give, 10^57 sol system atoms as observers doing a sample of a 500-bit trial every 10^-14 s [a fast chem rxn rate] is a Monte Carlo on steroids, and in effect gives a generous upper limit to what sampling in our solar system can do. No realistic sol system process can explore more of a config space than this. In short I am giving a limit based on number of possible chem rxn time events in our sol system on a reasonable lifespan. (Cf Trevors and Abel on the universal plausibility bound for more, here. Well worth reading -- rated, "highly accessed.") For the observable cosmos, we are looking at 1,000 bits exhausting sampling possibilities even more spectacularly. Now, go to much slower organic chem rxns in some Darwin's pond, comet, gas giant moon, etc. Pre-biotic situation. Note that hydrolysis and condensation rxns compete, there is generally no significant energetic reason to favour L- vs R-handed forms in ponds etc, there are cross-rxns, many of the relevant life reactions are energetically uphill (note ATP as molecular energy battery), we need to meet a fairly demanding cluster of organisation, process control etc. With the proteins coming in thousands of clusters in AA sequence space that are structurally unrelated, perhaps half needing to be there for the first working cell. Mix in chicken-egg loops for many processes, then impose a von Neumann kinematic self-replicator facility that uses codes, algorithmic step by step processes and more. No intelligently directed configuration permitted, per OOL model assumptions. Here are Orgel and Shapiro in their final exchange some years ago on the main schools of thought on OOL:
[[Shapiro:] RNA's building blocks, nucleotides contain a sugar, a phosphate and one of four nitrogen-containing bases as sub-subunits. Thus, each RNA nucleotide contains 9 or 10 carbon atoms, numerous nitrogen and oxygen atoms and the phosphate group, all connected in a precise three-dimensional pattern . . . . [[S]ome writers have presumed that all of life's building could be formed with ease in Miller-type experiments and were present in meteorites and other extraterrestrial bodies. This is not the case. A careful examination of the results of the analysis of several meteorites led the scientists who conducted the work to a different conclusion: inanimate nature has a bias toward the formation of molecules made of fewer rather than greater numbers of carbon atoms, and thus shows no partiality in favor of creating the building blocks of our kind of life . . . . To rescue the RNA-first concept from this otherwise lethal defect, its advocates have created a discipline called prebiotic synthesis. They have attempted to show that RNA and its components can be prepared in their laboratories in a sequence of carefully controlled reactions, normally carried out in water at temperatures observed on Earth . . . . Unfortunately, neither chemists nor laboratories were present on the early Earth to produce RNA . . . [[Orgel:] If complex cycles analogous to metabolic cycles could have operated on the primitive Earth, before the appearance of enzymes or other informational polymers, many of the obstacles to the construction of a plausible scenario for the origin of life would disappear . . . . It must be recognized that assessment of the feasibility of any particular proposed prebiotic cycle must depend on arguments about chemical plausibility, rather than on a decision about logical possibility . . . few would believe that any assembly of minerals on the primitive Earth is likely to have promoted these syntheses in significant yield . . . . Why should one believe that an ensemble of minerals that are capable of catalyzing each of the many steps of [[for instance] the reverse citric acid cycle was present anywhere on the primitive Earth [[8], or that the cycle mysteriously organized itself topographically on a metal sulfide surface [[6]? . . . Theories of the origin of life based on metabolic cycles cannot be justified by the inadequacy of competing theories: they must stand on their own . . . . The prebiotic syntheses that have been investigated experimentally almost always lead to the formation of complex mixtures. Proposed polymer replication schemes are unlikely to succeed except with reasonably pure input monomers. No solution of the origin-of-life problem will be possible until the gap between the two kinds of chemistry is closed. Simplification of product mixtures through the self-organization of organic reaction sequences, whether cyclic or not, would help enormously, as would the discovery of very simple replicating polymers. However, solutions offered by supporters of geneticist or metabolist scenarios that are dependent on “if pigs could fly” hypothetical chemistry are unlikely to help.
Mutual ruin, in short; what they probably did not tell you in HS or College Bio textbooks and lectures. This is the root of the iconic tree of life. It is chock full of FSCO/I, as Orgel and Wicken noted across the 1970's:
ORGEL: . . . In brief, living organisms are distinguished by their specified complexity. Crystals are usually taken as the prototypes of simple well-specified structures, because they consist of a very large number of identical molecules packed together in a uniform way. Lumps of granite or random mixtures of polymers are examples of structures that are complex but not specified. The crystals fail to qualify as living because they lack complexity; the mixtures of polymers fail to qualify because they lack specificity. [[The Origins of Life (John Wiley, 1973), p. 189.] WICKEN: ‘Organized’ systems are to be carefully distinguished from ‘ordered’ systems. Neither kind of system is ‘random,’ but whereas ordered systems are generated according to simple algorithms [[i.e. “simple” force laws acting on objects starting from arbitrary and common- place initial conditions] and therefore lack complexity, organized systems must be assembled element by element according to an [[originally . . . ] external ‘wiring diagram’ with a high information content . . . Organization, then, is functional complexity and carries information. It is non-random by design or by selection, rather than by the a priori necessity of crystallographic ‘order.’ [[“The Generation of Complexity in Evolution: A Thermodynamic and Information-Theoretical Discussion,” Journal of Theoretical Biology, 77 (April 1979): p. 353, of pp. 349-65. (Emphases and notes added. Nb: “originally” is added to highlight that for self-replicating systems, the blue print can be built-in.)]
The roots of the terms complex specified information, specified complexity and functionally specific complex organisation and associated information lie in this OOL context. Early design thinkers such as Thaxton et al built on this and Dembski et al and Durston et al, used statistical and information theory techniques to develop metric models. The simple model in the OP above allows us to understand how they work. and provide a useful threshold metric of functionally specified complexity that is not plausibly the result of blind chance and mechanical necessity on the gamut of sol system or observed cosmos. Where, for chemical interactions, the sol system is to first reasonable approximation our effective universe. It is patently maximally implausible to get to first cell based life meeting known requisites buy blind forces. Speculative intermediates depend on speculation or major investigator injections of intelligently directed contrivances. And, there is a paucity of the scope of results that would be required to give adequate empirical warrant to such an extraordinary claim. Including, recall, codes and algorithms plus matched executing machinery assembling themselves out of molecular agitation and thermodynamic forces in that pond or the like. The fact is, on trillions of test cases -- start with the Internet and a technological civilisation around us -- FSCO/I is a commonplace phenomenon and one where there is a reliably known, uniformly observed cause for it. One, consistent with the needle in haystack challenge outlined. Namely, the process of intelligently directed contingency, aka design. This more than warrants accepting FSCO/I as a reliable, inductively strong signature of design when we see it, even for cases where we do not have direct access to the observation of the causal process, e.g. the remote past of origins or an arson investigation etc. This is not even controversial generally, it is only because of the ideologically imposed demand and attempted redefinition of science and its methods in recent years . . . turning science and sci edu, too often into politics and propaganda . . . that there is a significantly polarised controversy and the sort of dismissive sneering schoolyard taunt contempt Th just exemplified. We speak here of inductive inference to the best current explanation, open to further observation and reasoned argument. If you disagree bring forth empirically backed evidence, as opposed to ideologised just so stories dressed up in lab coats. Turning to origin of major body plans, the degree of isolation in islands of function of protein domains in AA sequence space should give pause. The pop genetics to find and fix successive developmental muts should add to that. The number of co-ordinated muts to make a whale out of a land animal should ring warning bells. And the scope of genomes to effect body plans, 10 - 100+ mn bases, caps off for now. In short, we have an origins narrative that is clearly ideologically driven and lacks warranting observational evidence. It is deeply challenged to account for a common phenomenon, FSCO/I. One that happens to be pervasive in cell based life. One, whose observed origin, on trillions of cases, is no mystery: design. Yes, one may debate on merits and information theory based metrics. But in the end, the FSCO/I phenomenon is an empirical fact, not a dubious speculation. In examples in the living cell, we face digitally -- discrete state -- coded genetic information with many algorithmic features, and associated execution machinery that at that object code level, have to be very specifically co-ordinated. With kilobits to megabits and more of information to address, right in the heart of the living cell, in string data structures. With Nobel Prizes awarded for discovery and elucidation. So, what do you know about coded strings such as these in this thread, or in the chips in the computer behind what is on your screen, or in D/RNA? First, they are informational, and that coded information is functionally specific and measurably complex. This doc file has 369 kbytes, etc. Second, that info metrics take in selection and surprise from a field of possibilities, implying a log prob model, often on base 2 hence bits. Though, often the direct length of chain of y/n q's to specify state approach [7 y/n q's per ASCII character for familiar instance] gives essentially the same result. Hence again bits, binary or two state digits or elements. Redundancy in codes -- per familiar cases, u almost always follows q in English text and adds very little info, e is about 1/8 of English text, etc -- may reduce capacity somewhat but in the end does not materially affect the point. Third, that codes imply rules or conventions that communicate on assignment of symbolised states to meanings, which may be embedded in the architecture of a machine that effects machine code. The ribosome protein assembly system is a case of this. Fourth, that this is on the table at origin of cell based life. At its core. Design is at the table from OOL forward as a live option, whatever the ideologues may wish to censor. And, it is therefore at the table thereafter. And, would make sense out of a lot of things. Opening up many investigations and the prospect of reverse engineering and forward engineering. (Though, given the obvious dangers of molecular nanotech, that needs to be carefully regulated across this Century.) Nope, a science sparker not a science stopper. So, why should debates over Bernouilli-Laplace indifference and the like be seen as gotcha, lock up talking points . . .? (Apart from, ideologues looking for handy distractors to cloud and polarise an issue.) Sure, debate why we think any card has 1 in 52 chances, or any side of a die 1 in 6, or a coin 1 in 2, or the idea used by early stat mech thinkers that microstates to first approximation are equiprobable so the focus shifts to statistical weight of clusters. But recall, there is a more complex analysis that takes in distributions, and that Monte Carlo methods allow characterisation of pattens. Where, Durston et al are in effect arguing that across its span, life eplored the range of reasonably practical empirically warranted possibilities, reflected in the patterns we see in protein families. And more. KF PS: BTW, in decision theory, we don't usually assign a blind chance distribution to a decision node as intelligent deciders have purposes.kairosfocus
October 25, 2014
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KF - "Thorton, all you have done here is silly schoolyard taunting to play at erecting and knocking over a strawman. Strike one. KF" Well to be honest, that's what happens when you open the door and let a wild animal inside of a human dwelling who is not potty trained. He'll lift his leg and defecate anywhere he sees fit. Then turn right around growl, snarl and attack when you try and manage the situation. It's not like you folks were unaware of his/her animalistic behavior. If anything can be said of this individual, he is at least consistent in his disrespect of fellow man. It's not like he's ever pretended to hide anything or promise to behave. Allowing this amnesty thing to all those banned Sock-Puppets was like a rural land owner calling the Septic Tank Company and asking them to please come back and dump that load they pumped from your Tank onto your front lawn because you want to prove to all your neighbors and the whole world how ecologically responsible and sustainable you are. The resulting infections and diseases that followed that fateful decision proved what a fatal flaw that decision really was, even though the motive may have been a genuine one.DavidD
October 25, 2014
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Thorton, all you have done here is silly schoolyard taunting to play at erecting and knocking over a strawman. Strike one. KFkairosfocus
October 25, 2014
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KF's nonsense really needs to be retitled "Functional Information Associated with Specific Complex Organization" FIASCO for short.Thorton
October 24, 2014
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After a 14 billion year shake of its dice, the universe seems to have managed to create this here comment. Even in the config space of ascii characters in a comment box, that is quite impressive. But that is an artificial context. Truly the current configuration facilitating this comment was equiprobable with all other possible arrangements of constituent physical/material entities. Seems like usually things wind up in a state of equilibrium, rather than like this. Just hasn't been enough time for this. We need more universes. Infinite universes will do the trick.MrMosis
October 24, 2014
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DNA jock @ 207 Iam curious to know what other probability distribution would you use if there is no way of finding the probability of every possible state.the bystander
October 24, 2014
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kf, you said "So, with just 500 bits, we already have a supertask for the solar system’s atomic resources. 501 bits doubles the space’s scope and 1,000 bits would make for a haystack that would swallow up the observable cosmos." Likewise when you calculated “Your comment no 248 to me is 1071 characters, at 7 bits each, wel past the 500 bit threshold.” You appear to be assuming that every state in the config space is equiprobable; is this your assumption?DNA_Jock
October 24, 2014
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D-J, actually, I have done that for controlled cases (at request/challenge of MF years ago, it's in my always linked note through my handle and may be in the UD WACs). But the point is, why stop half way through the calc just to entertain those whose whole point is to obfuscate what is going on? Take the next step which reveals this is an info metric with a threshold. Info metrics, we have handled for seventy years. And the info beyond a threshold metric makes physical sense, that's why between VJT Paul Giem and I the Chi_500 metric popped out three and a half years back. If you wonder, think about a Monte Carlo sim set, it explores a population and captures the range of outcomes reasonably likely to be encountered in a dynamic system [explores across time/runs] . . . or if you have background reflect on an ensemble of duplicate systems as Gibbs did for stat thermod, looking at what is feasibly observable. So, we have a reasonable practical model that is easily validated. Give all 10^57 atoms of the solar system trays of 500 coins, flip the trays and observe every 10^-14 s, fast ionic rxn rate. Do for 10^17 s. You will be able to sample of the config space for 500 coins, 3.27*10^150 possibilities, about as one straw to a cubical haystack 1,000 light years across, about as thick as our galaxy's central bulge. Sampling theory tells us pretty quickly, that if such were superposed on our neighbourhood, with practical certainty we would blindly pick straw. We just are not able to sample a big enough fraction to make picking rarities up a practical proposition. And, precisely because FSCO/I comes because many correct parts have to be correctly arranged and coupled to achieve function, that tightly constrains configs. Equivalently, configs can be seen as coded sequences of Y/N q's, set in string data structures. What AutoCAD does, in effect. So, discussion on strings is WLOG. To get a handle, 500 bits is about 72 ASCII characters as are used for this text. Not a lot. So, with just 500 bits, we already have a supertask for the solar system's atomic resources. 501 bits doubles the space's scope and 1,000 bits would make for a haystack that would swallow up the observable cosmos. Sure, you can tag, big numbers and sneer. Rhetoric, not analysis. In Darwin's pond or the other usual OOL scenarios, there are just simple chemicals to begin, you need to get to a gated, encapsulated, protein using metabolic entity with string storage of DNA codes [and proteins come in thousands of super families deeply isolated in AA sequence space], with ribosomes ATP synthetase, and a von Neumann kinematic self replicator. And you have to get to that starting from physics, thermodynamics forces and chemistry, without intelligence. The degree of FSCO/I dwarfs the 500 - 1,000 bit toy scale thresholds we mentioned. Just genomes look like 100,000 - 1 mn bases. Where, if you want to argue incrementalism, you have to get to code based, taped storage, controlled constructor self replication, on empirically well grounded evidence. What we can reliably say is that there is per trillions of test cases and the needle in haystack analysis outlined, one known and plausible source: intelligently directed configuration, aka design. To move on to body plans and the other half of the protein domains, you are looking at 10 - 100+mn base prs per major body plan. The config spaces here are in calculator smoking territory. I know, you will have been assured with tree of life diags and stories that give the impression that there is a vast continent of functional forms easily traversed in increments that work all the way. False impression, starting from the degree of isolation of protein clusters in AA seq space. What has really driven the dominant school is ideological imposition, that starts on the concept that blind chance and mechanical necessity incrementally did it so anything that fits the narrative gets iconised. But, when you turn to the info issues that assurance evaporates. I hope that helps you at least understand some of where we are coming from. No this is not a little rhetorical gotcha game, some big unanswered issues lurk. And FSCO/I is at the heart of them. KFkairosfocus
October 24, 2014
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Soooo, kf, no calculation of p(T|H),despite the requests in posts 21, 39, and 42. Therefore, no calculation of CSI or FSCO/I. [crickets]DNA_Jock
October 24, 2014
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P: Probability calculation is not the issue. Blind sampling in a context driven by chance and mechanical necessity is . . . if you will, imagine a sort of real world, massively parallel Ulam Monte Carlo process in ponds, puddles and patches of oceans, comets, gas giant moons then multiply across our observed cosmos. The search capacity of that would be dwarfed by the 10^80 atoms, each with 1,000 coins flipped, read and functionally tested every 10^-14s (~ 1 cycle of red light). For 10^17 s. Such a search could not sample -- the search window, cf the illustration in the OP -- as much as 1 in 10^150 of the space of configs for 1,000 H/T coins. This is a very sparse search. The very same Monte Carlo thinking tells us the predictable, all but certain result: a needle in haystack search. So long as FSCO/I relevant to life forms is rare, such a process will with all but absolute certainty only capture the bulk, straw. That is, islands of function are not credibly findable on such a process as is imagined for abiogenesis. And similar searches confined to planetary or solar system scope are much more overwhelmed by the complexity challenge posed by body plans. Recall, the genome alone of a first cell is credibly 100 - 1,000 kbits, and that for new body plans, 10 - 100+ mn, based on reasonable estimates and observed cases. For each additional bit, the search space doubles . . . 500 bits is 3.27*10^150 possibilities, 1,000 is 1.07*10^301, 100,000 is 9.99 *10^30,102 possibilities and it gets worse and worse. The dismissive talking points fail. KFkairosfocus
September 9, 2014
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Still no response from Gordon Davisson... :|Upright BiPed
September 9, 2014
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Gpuccio, our ability to make valid probability calculations is limited because there is more than one kind of uncertainty. When we know all of the possible outcomes and a process is random, we can calculate it's probability. However, it's unclear how you can calculate if biological darwinism is probable unless you know what all the possible outcomes are. As I pointed out in a previous thread..
... probabilities can only be assigned based on an explanation that tells us where the probability comes from. Those numbers cannot be the probability of that explanation itself. They are only applicable in an intra-theory context, in which we assume the theory is true for the purpose of criticism.
For example, you seem to assume that, if we went back in time and evolution was "played back" again, we would end up with the same result because that was the intended result. But that's not evident in observations alone. Nor is it implied in evolutionary theory. That's one of the theories you first implicitly bring to those observations. Some problems could be solved by some other combination of proteins. So, working the probability backwards is only valid in the context of categorizing where proteins fall in an intra-theory context, rather being valid the context of that theory being true. Furthermore, what constitutes repetition is not a sensory experience. Rather, it comes from theories about how the world works, in reality. For example, we do not expect all organisms to be preserved in the fossil record. As such, what does not constitute observing a transitional is, in part, based on the theory of paleontology, which includes the conditions in which we think fossilization occurs, etc. So, I'd ask, how is it that you know all the possible outcomes by which to calculate if evolution is probable?Popperian
September 7, 2014
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gpuccio:
Errata corrige: “we have at least 2000 unrelated and independent functional islands” (not 200!)
Given the theory that all these families must be related, how likely is that!Mung
September 6, 2014
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For those interested in reading gpuccio’s insightful comments on the dFSCI concept, here are the post #s within this thread: 133, 140, 146, 149, 152, 173-175, 189, 190, 192-196.Dionisio
September 5, 2014
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KF @ 198 Maybe that relates to the OP on procedures that GP is working on, which could be another technical checkmate (++) in all these discussions? Next, GP could sing: lasciatemi cantare con la chitarra in mano lasciatemi cantare una canzone piano piano while waiting for the interlocutors to recover from the shock :)Dionisio
September 4, 2014
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GP: Where also the search/config space issue sits on the table as well as the extensions that we are looking at codes, algorithms and associated execution machinery in a von Neumann self replicating automaton. KFkairosfocus
September 4, 2014
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#193 gpuccio
If you agree (as you seem to agree) that we have at least 2000 unrelated and independent functional islands in the proteome (the superfamilies), that means that the “successful” search has happened 2000 times independently. So, even in this highly imaginary scenario, the probability of getting 2000 successes would be approximately 10^20000. Quite a number, certainly untreatable by any realistic probabilistic system with realistic probabilistic resources. A number with which no sane scientist wants to deal.
:)Dionisio
September 4, 2014
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Gordon Davisson: Now, the next argument: "The empirical argument: overview"
Now, I want to turn to the empirical side of your argument: that we’ve never seen dFCSI produced without intelligence, which is evidence that it cannot be produced without intelligence. There are a number of complications here, but I want to concentrate on what I see as the big problem with this: we can only infer the nonexistence of something from not detecting it if we should expect to detect it. We’ve never actually seen an electron; but given how small they are, we don’t expect to be able to see them, so that’s not evidence they don’t exist. We’ve only seen atoms fairly recently, but that didn’t count as evidence against their existance for the same reason. On the other hand, if we’d gotten to the point where we should be able to see them, and hadn’t… then that would have been evidence against them. We’ve never seen a supervolcano erupt; that should be really easy to detect, but they’re rare enough that we don’t expect to have seen one anyway.
I am not sure that I understand your argument here. My argument is that dFSCI, out of the biological world, is never observed without design, and is observed in tons when it comes from a design process. It is not, and never has been, that dFSCI is never observed. So, if we never observe a supervolcano erupt in normal circumstances, and then we see that a lot of supervolcanos erupt each time, say, there is an earthquake of at least some magnitude, it would be very reasonable to assume that there is a sound relationship between big earthquakes and supervolcano eruptions. So, my argument is not that we never see dFSCI, but rather that we see it a lot, and always in designed things. Then you say:
In the case of completely novel genes, I’d expect them to be both rare and hard to detect, so making an empirical case against them is going to be very difficult.
But again, the point here is not that completely novel genes are not observed. There are a lot of them. As we have said, all the 2000 superfamilies were completely novel genes when they appeared. And they are not hard to detect. Remember, the point is not to see a novel gene appear now. It is to explain how novel genes appeared at definite times in natural history, and how they can express dFSCI against all probabilistic rules and all known algorithms. Finally, you say:
But let me take care of a minor issue. I’m going to be referring fairly extensively to the Lenski experiment, so I want to clarify my stance on its results. You said: "First of all, I hope we agree that no dFSCI at all has emerged from the Lenski experiment. At most, loss of function has come out. And the small regulatory change about citrate." I have to disagree about the loss of function statement. At least as I understand it, a new functional connection was made between duplicates of two pre-existing functional elements (a gene and a regulatory sequence), creating a new function. This is certainly not a new functional gene (your main concern), but I’d argue it’s a gain of function and (at least as I understand it) a gain of dFSI (the continuous measure) if not dFSCI.
Perhaps I have not been clear. I said: "At most, loss of function has come out. And the small regulatory change about citrate." I did not mean that the regulatory change about citrate is loss of function (it could be, but I am not interested in analyzing that aspect). What I meant was that, apart from the regulatory change, the rest is mainly loss of function. I was referring to this: (from Wikipedia)
In the early years of the experiment, several common evolutionary developments were shared by the populations. The mean fitness of each population, as measured against the ancestor strain, increased, rapidly at first, but leveled off after close to 20,000 generations (at which point they grew about 70% faster than the ancestor strain). All populations evolved larger cell volumes and lower maximum population densities, and all became specialized for living on glucose (with declines in fitness relative to the ancestor strain when grown in dissimilar nutrients). Of the 12 populations, four developed defects in their ability to repair DNA, greatly increasing the rate of additional mutations in those strains. Although the bacteria in each population are thought to have generated hundreds of millions of mutations over the first 20,000 generations, Lenski has estimated that within this time frame, only 10 to 20 beneficial mutations achieved fixation in each population, with fewer than 100 total point mutations (including neutral mutations) reaching fixation in each population
Emphasis mine.gpuccio
September 4, 2014
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Gordon Davisson: Another correction: "even more optimistic than the false estimates I have discussed previously", not "preciously"! I suppose my narcissism pulled a subconscious trick on me. :)gpuccio
September 4, 2014
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Gordon Davisson: Errata corrige: "we have at least 2000 unrelated and independent functional islands" (not 200!)gpuccio
September 4, 2014
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