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Selection, structure and the heritability of behaviour

2002· article· en· W2116885251 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Evolutionary Biology · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsMcGill University
Fundersnot available
KeywordsHeritabilityBiologySelection (genetic algorithm)Genetic variationGenetic correlationDominance (genetics)Variance componentsAdditive genetic effectsQuantitative geneticsVariation (astronomy)StatisticsEvolutionary biologyGeneticsMathematics

Abstract

fetched live from OpenAlex

Abstract Characters which are closely linked to fitness often have low heritabilities (VA/VP). Low heritabilities could be because of low additive genetic variation (VA), that had been depleted by directional selection. Alternatively, low heritabilities may be caused by large residual variation (VR=VP – VA) compounded at a disproportionately higher rate than VA across integrated characters. Both hypotheses assume that each component of quantitative variation has an independent effect on heritability. However, VA and VR may also covary, in which case differences in heritability cannot be fully explained by the independent effects of elimination-selection or compounded residual variation. We compared the central tendency of published behavioural heritabilities (mean=0.31, median=0.23) with morphological and life history data collected by Mousseau & Roff (1987). Average behavioural heritability was not significantly different from average life history heritability, but both were smaller than average morphological heritability. We cross-classified behavioural traits to test whether variation in heritability was related to selection (dominance, domestic/wild) or variance compounding (integration level). There was a significant three-way interaction between indices of selection and variance compounding, related to the absence of either effect at the highest integration level. At lower integration levels, high dominance variance indicated effects of selection. It was also indicated by the low CVA of domestic species. At the same time CVR increased disproportionately faster than CVA across integration levels, demonstrating variance compounding. However, neither CVR nor CVA had a predominant effect on heritability. The partial regression coefficients of CVR and CVA on heritability were similar and a path analysis indicated that their (positive) correlation was also necessary to explain variation in heritability. These results suggest that relationships between additive genetic and residual components of quantitative genetic variation can constrain their independent direct effects on behavioural heritability.

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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.217
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it