The degree of embryonic development influenced some eggshell characteristics of wild Red-tailed Hawks (<i>Buteo jamaicensis borealis</i>)
Bibliographic record
Abstract
The influence of embryonic development on eggshell characteristics of wild birds, particularly raptors, is not well studied. Red-tailed Hawk (Buteo jamaicensis borealis (Gmelin, 1788)) eggs (n = 66) collected in central New York State (USA) during the late 1800s and early 1900s were examined to determine if eggshell mass, eggshell thickness, and a thickness index corrected for egg shape and blowhole size were influenced by the degree of embryonic development at the time of collection. Changes in these characteristics were examined with linear mixed models with year of collection and clutch size specified as random variables. Unexpectedly, length, breadth, and mass of eggshells were greater in eggs with advanced embryonic development than eggs with less developed embryos, perhaps due to sampling error or collector bias. Eggs containing well-developed embryos were 13% thinner and had a thickness index 7% smaller than eggs with poorly developed embryos. Eggs with larger embryos had larger blowhole diameters; this relationship may be useful in determining degree of embryonic development in eggs of other species where development information is not explicit. Given the historical and current interest in eggshell thinning due to pollutants, degree of embryonic development should be accounted for in studies of eggshell characteristics.
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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 | 0.000 |
| 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".