Multi-Year Seasonal Sex-Allocation Patterns in Red-winged Blackbirds (<i>Agelaius phoeniceus</i>)
Bibliographic record
Abstract
A previous study reported that climate-mediated increases in the length of the breeding season produced increasingly female-biased fledging sex ratios in Red-winged Blackbirds (Agelaius phoeniceus). Using those same data plus one additional year (11 years in total), I found that this phenomenon was not a result of greater production of females early and late in the season, contrary to what had been proposed. Instead, seasonal sex-allocation patterns interacted with season length. Early and midseason sex ratios became more female-biased as breeding seasons became longer, whereas late-season sex ratios tended to vary in the opposite manner, albeit weakly. Thus, the discrepancy between sex ratios late in the season and those earlier (early plus midseason) was a strong function of season length. Because fledging sex ratios did not vary with nestling mortality, these patterns appear to be a consequence of nonrandom sex-allocation rather than sex-biased survival. It is unclear whether these sex-allocation patterns are adaptive. Because the climatic factor (the North Atlantic Oscillation) associated with longer breeding seasons is also associated with higher winter mortality, however, it is possible that female Red-winged Blackbirds change how they allocate sex in response to changes in the breeding sex ratio. If climate change continues to alter these patterns, documenting how individuals and populations respond will be informative, from both basic and applied perspectives.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".