A SCALE-DEPENDENT EXAMINATION OF STOPOVER DECISIONS IN MIGRATORY PASSERINES AT LONG POINT, ONTARIO
Bibliographic record
Abstract
Stopovers, periods o f rest and refuelling between migratory flights, play an integral role in determining fitness o f migrating passerines. Migration success is dependent on decisions made about when to arrive and leave particular stopover sites and how to utilize regional landscapes. I used mark-recapture analysis o f bird banding data from a stopover site and direct measurements from radio telemetry data covering a stopover landscape of~20 x 40 km at Long Point, Ontario, to examine stopover decisions. Specifically, I estimated probabilities that individuals would leave a site in relation to age, fat stores, season, and the extent to which decisions made in the landscape influence decisions at particular sites. I found decisions to leave a stopover site are largely age-dependent regardless of fat stores or season with adults having higher departure probabilities than young. Additionally, these initial decisions are primarily determined by landscape scale decisions prior to landfall although divergent life histories favour different strategies. Knowledge of the evolution and ecology of migration and for conservation o f migratory passerines requires an integrated understanding o f how migrants use local sites and broad landscapes to optimize their migration.
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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 | 0.001 | 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".