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Record W2101747139 · doi:10.1638/2008-0172.1

Plasma Biochemistry Values in Emperor Geese (Chen canagica) in Alaska: Comparisons Among Age, Sex, Incubation, and Molt

2009· article· en· W2101747139 on OpenAlexaboutno aff
J. Christian Franson, David J. Hoffman, Joel A. Schmutz

Bibliographic record

VenueJournal of Zoo and Wildlife Medicine · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
Fundersnot available
KeywordsFeatherBiologyIncubationMoultingEmperorPopulationAnimal scienceIncubation periodZoologyEcologyDemographyBiochemistry

Abstract

fetched live from OpenAlex

Reduced populations of emperor geese (Chen canagica), a Bering Sea endemic, provided the need to assess plasma biochemistry values as indicators of population health. A precursory step to such an investigation was to evaluate patterns of variability in plasma biochemistry values among age, sex, and reproductive period. Plasma from 63 emperor geese was collected on their breeding grounds on the Yukon-Kuskokwim Delta in western Alaska, USA. The geese sampled included 18 incubating adult females captured, in mid June, on their nests by using bow nets, and 30 adults and 15 goslings captured in corral traps in late July and early August, when the adults were molting their wing feathers and the goslings were 5-6 weeks old. Plasma was evaluated for 15 biochemical parameters, by comparing results among age, sex, and sampling period (incubation versus wing-feather molt). Ten of the 15 biochemical parameters assayed differed among adults during incubation, the adults during molt, and the goslings at molt, whereas sex differences were noted in few parameters.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.255
Teacher spread0.244 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations14
Published2009
Admission routes1
Has abstractyes

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