Data from: Are there synergistic or antagonistic effects of multiple maternally-derived egg components (antibodies and testosterone) on offspring phenotype?
Bibliographic record
Abstract
Eggs are multivariate in that they contain multiple maternally-derived egg components (e.g. hormones, antibodies, mRNA, antioxidants) which are thought to influence offspring phenotype. However, most studies have focused on single egg components and on short-term effects. Here, we simultaneously manipulated two egg components, maternally-derived antibodies (MAb) and yolk testosterone (T) to assess potential synergistic or antagonistic effects on offspring phenotype from hatching to sexual maturity. We found no evidence for short-or long-term effects of either MAb or yolk T alone, or their interaction, on hatching mass, size at fledging (tarsus), body mass at sexual maturity (day 82), chick survival, humoral immune function, or any measured female reproductive trait at sexual maturity. There was a positive effect of yolk T, but not MAb, on offspring PHA response at 26 days of age but at 82 days of age MAb, but not yolk T, had a positive effect on PHA response. There was also a MAbsex interaction on 30 day chick mass, and a positive effect of yolk T on male courtship behaviour at sexual maturity. However, we found no evidence for synergy, i.e. where offspring treated both with MAb and yolk T had higher trait values than offspring treated with either MAb or yolk T alone for any measured trait. Similarly, evidence for antagonistic (compensatory) effects, where offspring treated both with MAb and yolk T had intermediate trait values compared with offspring treated with either MAb or yolk T alone, was equivocal.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.190 | 0.064 |
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 source (direct Gemma or distilled Codex), 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".