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Record W2803219895 · doi:10.2981/wlb.2003.029

Field methods to assess pectoral muscle mass in moulting geese

2003· article· en· W2803219895 on OpenAlexaboutno aff
Jens Nyeland, Anthony David Fox, Johnny Kahlert, Ole Roland Therkildsen

Bibliographic record

VenueWildlife Biology · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsnot available
FundersMinistry of Environment
KeywordsPectoral muscleMoultingBiologyAnatomyPectoralis MuscleGooseFlight featherZoologyEcology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.912
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.081
GPT teacher head0.358
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2003
Admission routes1
Has abstractyes

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