https://w3id.org/np/RAK0AOLorOrLMS_ra2At5u6C1jAthOrBlcIHVPrdADTr4
.trig | .trig.txt | .jelly | .jelly.txt | .jsonld | .jsonld.txt | .nq | .nq.txt | .xml | .xml.txt
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sub:assertion {
<https://w3id.org/delphi/resource/assessment/levin-2023-competency-05--claim-test>
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dc:description "analysis.py imports run() from the levin-2023-competency-04 re-implementation and re-runs hardwired and competency 20, 100 and 400 populations, 100 repeats of 250 generations each, from a new master seed. It compares best genotypic fitness at generation 250 with hardwired by one-sided Welch t-tests, measures the change in the mean genotypic curve between generations 126-150 and 226-250, the across-repeat SD of best genotypic fitness over generations 51-250 per level, and best phenotypic fitness at generation 250.";
<http://www.w3.org/2000/01/rdf-schema#comment> "Measured: 0.583921 mean best genotypic fitness at generation 250, competency 400 (hardwired: see extra) (n = 100, Monte Carlo; fixed seed, deterministic for a given numpy version). Interpretation: Simulation-result claim, tested by replication. 'Genotypic fitness of the best individual' is taken, as in the authors' Exp1 code, as the maximum pre-development fitness in the population each generation. 'Plateaued' is operationalised as < 0.03 change in the repeat-mean curve between generations 126-150 and 226-250; 'wider variance' as the across-repeat SD of best genotypic fitness averaged over generations 51-250; 'high phenotypic fitness' as mean best phenotypic fitness >= 0.95 at generation 250. 'Reduced selective pressure on structural genes' is the authors' interpretation of the lower plateau and is not measured separately.";
<http://www.w3.org/2000/01/rdf-schema#label> "Claim test of levin-2023-competency-05: supports, confidence 0.9";
<http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://github.com/fractastical/delphisci/blob/bf2af6ee0a84e23ffa6414ad7a0a50a8c276506e/test-data/claim-tests/levin-papers/levin-2023-competency-05/result.json>;
prov:wasAttributedTo <https://w3id.org/delphi/resource/agent/delphisci-claim-tester-claude-opus-5-5>;
<https://w3id.org/delphi/ontology/admissibleDatasets> "Runs of the model exactly as specified in the paper and its supplement (50-cell arrays, 100 embryos, top-10% phenotypic selection, crossover, mutation probability 0.6, competency 20/100/400); unspecified details from the authors' public code; fresh random seeds independent of the companion test levin-2023-competency-04.";
<https://w3id.org/delphi/ontology/assessmentType> "claim-test/0.1.0";
<https://w3id.org/delphi/ontology/dataKind> "computational";
<https://w3id.org/delphi/ontology/disconfirmingObservation> "Competent genotypic fitness reaching or exceeding hardwired, continuing to climb, or showing less spread at higher competency.";
<https://w3id.org/delphi/ontology/evidenceAgainst> "All pre-registered criteria hold: genotypic fitness at generation 250 is 0.973, 0.872 and 0.584 at competency 20, 100 and 400 vs 1.000 hardwired (all p < 1e-80); the curves change by < 0.003 between the two windows; across-repeat SD rises 0.0040 < 0.0094 < 0.0211; phenotypic fitness is 1.0 at every level.",
"How long genotypic fitness tracks hardwired before plateauing depends strongly on competency: the competent mean first falls 0.02 below hardwired at generation 85, 33 and 6 for competency 20, 100 and 400. 'Rose briefly' fits competency 400 best; at competency 20 the genotypic curve follows hardwired for most of the climb.",
"The companion test levin-2023-competency-04 had already reported generation-250 genotypic means (0.97, 0.87, 0.59) before this test was pre-registered, so the direction of criterion A was known; this run uses independent seeds.",
"The repository was restructured while this test ran (claim-tests/ moved to test-data/claim-tests/, books/ to claim-sources/); the pre-registered planned_datasets keep the old paths.",
"This is a replication of a simulation, not an empirical test: it shows what follows from the stated model, not what real cellular competency does.";
<https://w3id.org/delphi/ontology/expectedObservation> "Competent populations' best genotypic fitness rises for a few generations, then flattens below the hardwired curve, with across-repeat spread increasing with competency level and phenotypic fitness near maximal.";
<https://w3id.org/delphi/ontology/failCriterion> "Pre-registered: refutes if any competent level's mean best genotypic fitness at generation 250 is >= hardwired, or the generation-51-250 SD at competency 400 is below that at competency 20, or any competent level's genotypic mean curve still rises by more than 0.1 between the 126-150 and 226-250 windows. Any other failure of (A)-(D) -> mixed.";
<https://w3id.org/delphi/ontology/hasConfidence> "0.9"^^xsd:double;
<https://w3id.org/delphi/ontology/hasEvidence> <https://w3id.org/delphi/resource/evidence/levin-2023-competency-05--claim-test--dataset-1>,
<https://w3id.org/delphi/resource/evidence/levin-2023-competency-05--claim-test--dataset-2>,
<https://w3id.org/delphi/resource/evidence/levin-2023-competency-05--claim-test--dataset-3>;
<https://w3id.org/delphi/ontology/hasVerdict> "supports";
<https://w3id.org/delphi/ontology/hypothesis> "In a re-run of the Shreesha & Levin (2023) Experiment 1 model (fixed competency 20/100/400 vs hardwired, 100 repeats x 250 generations), the best genotypic fitness of each competent population stops rising and stays below the hardwired population's, its spread across repeats grows with competency, while phenotypic fitness stays high.";
<https://w3id.org/delphi/ontology/inferenceMethod> "Mean curves over 100 repeats; one-sided Welch t-test at generation 250 (alpha 0.001); plateau as window-mean difference < 0.03; spread as mean across-repeat SD over generations 51-250 compared across levels.";
<https://w3id.org/delphi/ontology/passCriterion> "Pre-registered, with 'best genotypic fitness' = the maximum genotypic (pre-development) fitness in the population each generation, as in the authors' code: (A) at generation 250 each competent population's mean best genotypic fitness is below hardwired, one-sided Welch t-test p < 0.001; (B) plateau: for each competency level, |mean of the mean curve over generations 226-250 minus mean over generations 126-150| < 0.03; (C) the across-repeat standard deviation of best genotypic fitness, averaged over generations 51-250, is strictly ordered competency 20 < 100 < 400; (D) mean best phenotypic fitness at generation 250 >= 0.95 for every competency level. All four -> supports.";
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dc:description "per-generation best genotypic and phenotypic fitness; mean and SD curves in derived/genotypic_curves.json";
dc:license "";
<http://www.w3.org/2000/01/rdf-schema#label> "Dataset: Re-run of the Shreesha & Levin (2023) Experiment 1 re-implementation, 100 repeats x 250 generations x 4 populations (generated by analysis.py)" .
<https://w3id.org/delphi/resource/evidence/levin-2023-competency-05--claim-test--dataset-2>
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dc:description "model specification (Sections 2-3, Discussion); full text vendored in claim-sources/levin-papers/inputs/2023-competency.txt";
dc:license "CC BY 4.0";
<http://www.w3.org/2000/01/rdf-schema#label> "Dataset: Shreesha L, Levin M (2023) Cellular Competency during Development Alters Evolutionary Dynamics in an Artificial Embryogeny Model. Entropy 25(1):131";
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dc:description "definition of the tracked 'best genotypic fitness' (population maximum) and unspecified model details; not imported";
dc:license "";
<http://www.w3.org/2000/01/rdf-schema#label> "Dataset: Authors' simulation code for Shreesha & Levin (2023), CellularCompetency";
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