Crosswinds During Spring Migration Carryover and Influence the Time Interval Between Arrival and Laying in a Neotropical Migrant
Bibliographic record
Abstract
) is linked to weather conditions on migration, specifically the speed of crosswinds experienced over the western flyway during a 2-week period from May 18 to 31. During 2015-2017, we investigated whether this carryover effect was due to crosswind effects on the timing of arrival, the reproductive state and mass of females on arrival, or a combination of other effects that delayed egg laying. In these years, female arrival dates varied with age but were independent of year, growing degree days, or crosswinds on migration. Though crosswinds experienced by females during the 14-day period before their arrival on the breeding ground had no significant effect on their reproductive state (plasma triglyceride levels) or mass (controlling for tarsus length) on arrival, crosswinds had an effect on the time interval between arrival and egg laying. The time interval between arrival and egg laying was also shorter if females arrived with elevated plasma triglyceride levels and longer if females arrived early in the season. Carryover effects from crosswinds experienced during migration on the timing of breeding and reproductive success of yellow warblers are likely to arise due to their effect on arrival date and how rapidly birds can transition from a migratory to a reproductive physiological state. Both wind-speed experienced on migration (14 days before arrival) and reproductive state on arrival (plasma triglyceride concentration) independently influenced the time interval between arrival and egg laying. Crosswinds that delay breeding have a significant effect on reproductive success; female yellow warblers that initiate reproduction late decrease both their chance to raise at least one nestling and the number of nestlings fledged.
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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 | 0.001 |
| 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) | 0.002 | 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".