Field methods to assess pectoral muscle mass in moulting geese
Bibliographic record
Abstract
In this paper, we report two new simple field methods to assess changes in pectoral muscle mass in live moulting geese. In the first method, transverse chest profiles of Canada geese Branta canadensis and greylag geese Anser anser were recorded using soldering wire. This standard measure of the chest angle showed a highly significant relationship with actual pectoral muscle mass. Chest angle measures showed a highly significant polynomial correlation with an index of moult stage, i.e. length of the ninth primary (p9). This indicated an initial slight decline in pectoral muscle mass as p9 length increased, followed by an increase in muscle mass in preparation for regaining the ability to fly. In the second method, visual pectoral profile scores from 0 (thin pectoral muscles concave) to 3 (convex bulky) recorded at distances using telescope or binoculars also proved to be useful as a field measure of pectoral muscle mass in moulting geese. Hence, the first method provides a non‐consumptive means of predicting pectoral muscle mass in moulting geese without the need to dissect birds, and the second method enables field prediction of muscle mass in moulting geese without resort to capture of birds.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".