Data from: Combined effects of cold snaps and agriculture on the growth rates of Tree Swallows (<em>Tachycineta bicolor</em>)
Bibliographic record
Abstract
The decline of avian aerial insectivores has been greater than any other foraging guild and both climate change and agricultural intensification are leading hypotheses explaining this decline. Spring cold snaps are predicted to increase in frequency due to climate change, and factors associated with agricultural intensification (e.g., toxicological agents, simplification of agricultural landscapes, and reductions of insect prey) potentially exacerbate the negative effects of cold snaps on aerial insectivore nestling growth and body condition. We evaluated this hypothesis using repeated measures of Tree Swallow (Tachycineta bicolor (Vieillot, 1808)) nestling body mass and 9th primary length across an expansive gradient of agricultural intensification. Growth rate, asymptotic body mass, and near-fledging 9th primary length were lower for nestlings in landscapes consisting of more agro-intensive monocultures. This 14-year dataset of body measures occurring at 2, 6, 12, and 16 days of age showed that the negative impact of cold snaps on the growth of these two traits was stronger for nestlings reared in more agro-intensive landscapes. Our findings provide further evidence that two of the primary hypothesized drivers for the decline of many aerial insectivores may interact and aggravate their decline by reducing fledging survival.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.016 |
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".