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Record W2109569513 · doi:10.1525/cond.2013.120175

Duration and Phenology of Remigial Molt of Barrow's Goldeneye

2013· article· en· W2109569513 on OpenAlexaffabout
Danica Hogan, Daniel Esler, J. E. Thompson

Bibliographic record

VenueOrnithological Applications · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsGolder Associates (Canada)Ducks Unlimited CanadaSimon Fraser UniversityBirds Canada
Fundersnot available
KeywordsWaterfowlPhenologyBiologyAnimal scienceEcologyZoologyDemography

Abstract

fetched live from OpenAlex

We quantified the duration and phenology of remigial molt of Barrow's Goldeneyes (Bucephala islandica) in northwestern Alberta, Canada. We estimated that the remiges' average (± SE) growth rate was 3.94 ± 0.13 mm day-1, slightly slower than that of most waterfowl. Barrow's Goldeneyes regained flight with the ninth primary 77% grown, a percentage similar to or greater than that of most waterfowl. By several metrics, remigial molt of Barrow's Goldeneye was longer than that of most waterfowl. We estimated that it took 6.5 ± 1.2 days for a new ninth primary to become visible once the old primary was dropped (pre-emergence interval). The periods in which males and females were flightless were 30 ± 0.4 and 28 ± 0.5 days, respectively, and 36.5 ± 0.5 and 34.5 ± 0.8 days, respectively, including the pre-emergence interval. Complete maturation of primaries after emergence took 39 ± 0.5 and 36 ± 0.7 days for males and females, respectively, and 45.5 ± 0.6 and 42.5 ± 0.9 days, respectively, including the pre-emergence interval. These results suggest a lack of strong selective pressure to reduce the duration of remigial molt in this species. Initiated over a range of nearly 2 months, remigial molt was asynchronous both between and within age and sex cohorts, suggesting a lack of strong temporal optima for remigial molt of Barrow's Goldeneyes at our study sites.

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)0.000
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 score0.135
Threshold uncertainty score0.268

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.010
GPT teacher head0.226
Teacher spread0.217 · 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

Citations3
Published2013
Admission routes2
Has abstractyes

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