Causes and consequences of variation in incubation behaviour in the Canada jay (Perisoreus canadensis), a winter-nesting boreal passerine
Bibliographic record
Abstract
Understanding of avian incubation is primarily gained from species nesting during spring and summer, under conditions markedly different from those prevailing in late winter. Using nest temperature loggers, we explored how ambient temperature and rainfall influenced off-bout frequency and off-bout duration and how incubation metrics influenced nest success of female Canada jays, a resident of boreal and subalpine forests that incubates eggs under sub-zero temperatures. Females spent 95.3 % ± 0.1 of their time incubating, and variation in attentiveness was driven primarily by variation in off-bout frequency than duration. Females took longer, less frequent off-bouts during warmer days and females that experienced high rainfall took shorter off-bouts. Nest success was negatively related to off-bout frequency but not duration. Our results suggest that attentiveness of females is driven by, and adjusted to, adverse conditions of late winter whereas low off-bout frequencies are driven by the need to avoid attracting nest predators.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".