Genetic, maternal, and environmental variance components for body weight and length of Atlantic cod at 2 points in life1
Bibliographic record
Abstract
Variance components were estimated for 2 body size traits of Atlantic cod at 2 time points. Wild-caught founders from 3 regions off eastern North America were spawned and their progeny were reared at 2 locations in 2 consecutive years. Full-sib families (n = 148) were kept separate until individuals achieved a size large enough to be tagged. At that time (220 d of age), BW and length of 47,637 offspring from 90 sires and 89 dams were recorded. The juveniles were then transferred to sea cages at 3 sites, where they grew further for more than a year. A second set of measurements was collected on 11,839 fish (634 d of age). Dispersion parameters were estimated using REML in bivariate analyses. Models included fixed degree-days (covariate), year × location subclasses, and genetic groups composed of connected families within region of origin. Random factors were animal (additive genetic effects), considering known relationships among the fish; dam (maternal effects); and family (effects common to full-sibs). At tagging, heritability estimates were small to moderate (0.15 and 0.24 for BW and length, respectively; SE = 0.14), similar to or somewhat larger than the proportions of variation ascribed to dams and families (11 to 16%). Later, heritability estimates were greater (0.27 ± 0.08 and 0.31 ± 0.09 for BW and length, respectively), whereas dam and family variance proportions were very small (3 to 4%). Omitting maternal or family components substantially increased the values obtained for heritability at both time points. At the later point, failure to account for maternal effects inflated heritability estimates by about 24% for both traits; ignoring family effects had double the impact. These effects persisted even though endogenous feeding lasts only a couple of weeks in this species and the fish had been pooled since tagging. Discarding data from parents that were completely confounded with their mates decreased heritability estimates slightly (by 0.04, for both traits) at the second point, with no loss of precision despite 15% fewer records and 34% fewer parents; the improved design seemed to have more fully disentangled the additive genetic effects. Estimates of genetic correlations between traits and between time points were very large (>0.89). The results imply that genetic variation exists for body size of cod at both stages. Poor data structure and inadequate models can potentially lead to overstatement of heritability, and thus also of the predicted selection response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".