It’s not all about temperature: breeding success also affects nest design
Bibliographic record
Abstract
Abstract There are numerous observational studies on intraspecific variation in avian nest building and a single experimental manipulation. The general consensus is that birds build nests in response to environmental conditions, but it is not clear whether such flexibility in nest building is reproductively advantageous. To test the relationship between building flexibility and reproductive success, we allowed captive zebra finches to build their first nest, using string, and to breed in temperature-controlled rooms held at 14 or 30 °C. Once the offspring had fledged, we returned half the pairs to breed at the same temperature while half the pairs were switched to the alternative temperature. We provided all pairs with string and left them to build and breed a second time. For their first nest, pairs that built at 14 °C used more string than did pairs that built at 30 °C, and pairs that bred successfully built a nest with more string than did unsuccessful pairs. When pairs built their second nest, however, temperature no longer explained the number of pieces of string they used; rather, irrespective of the ambient temperature, pairs that had successfully produced young from their first nest used the same amount of string for their second nest, whereas those that had failed to reproduce with their first nest used more string. These latter pairs were then more likely to reproduce successfully. Ambient temperature, therefore, did affect the nest the pairs built but only in the absence of reproductive experience.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".