Use of discrete molting grounds by migrant passerines undergoing prebasic molt in southern Quebec
Bibliographic record
Abstract
We documented prebasic flight feather molt of passerines captured in fall 2013 and 2015 at McGill Bird Observatory (MBO) in Montreal, Quebec. We recorded active molt of flight feathers (remiges) in 11 species that do not breed on site. Flight feather molt was frequent among Swainson's Thrush (Catharus ustulatus; 64% of adults), Tennessee Warbler (Oreothlypis peregrina; 57%), Nashville Warbler (Leiothlypis ruficapilla; 67%), and Yellow-rumped Warbler (Setophaga coronata; 44%), and was observed less frequently in other species. The minimum stopover length of molting individuals was on average 8 times longer than that of non-molting individuals of the same species. Among Swainson's Thrushes and Yellow-rumped Warblers, far more females were undergoing molt than males, whereas for Tennessee Warblers molt was slightly more frequent among males. Frequency of molt was similar between years for most species but not Yellow-rumped Warbler, with 59% of adults captured in 2013 molting compared to none in 2015. We also observed molting site fidelity with multiyear returns of Tennessee and Nashville warblers. The use of separate breeding and molting sites is not well understood among eastern North American species, and with recent studies highlighting the importance of molt locations in western North America, we demonstrate the value in additional study of the use of discrete molt locations in the East.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".