Causes and consequences of variation in diet composition of nestling Canada jays
Bibliographic record
Abstract
Diet quality during development can impact growth, physiology, behaviour and survival. The Canada jay is a resident boreal passerine that caches a wide variety of perishable food items in late summer and autumn for its over‐winter survival and late‐winter reproduction. A previous experiment found evidence that food supplementation of Canada jay pairs during the nestling period had a positive effect on the condition of their nestlings. However, given that foods cached by adults vary widely in nutritional content, the composition of nestling diets could also have an important influence on offspring development. In a population of Canada jays in Algonquin Provincial Park, Ontario, Canada, we investigated the influence of environmental conditions before and during the breeding season on nestling diet composition and the consequences of nestling diet composition on the body condition of nestlings and on their subsequent survival. Using stable‐carbon (δ 13 C) and ‐nitrogen (δ 15 N) isotopes, we estimated the proportion of three food groups (vertebrates + human food, invertebrates and plants) in feathers from almost 200 nestlings. Nestling diet in March and April was influenced by environmental conditions 5–6 months prior to hatching, with warmer and more variable autumn temperatures associated with a greater proportion of vertebrate flesh and human food in the diet. However, the proportion of vertebrates and human food in the diet had no influence on nestling body condition or whether an individual was observed the following fall. Our results, in conjunction with previous work on Canada jays, suggest that the quantity of food available to a nestling during development may be more important than diet composition.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".