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Record W1004138092

Nesting ecology of tundra swans on the coastal Yukon-Kuskokwim Delta, Alaska

2002· article· en· W1004138092 on OpenAlexaboutno aff
Colleen A. Babcock, Ada C. Fowler, Craig R. Ely

Bibliographic record

VenueWaterbirds · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
Fundersnot available
KeywordsTundraNest (protein structural motif)Avian clutch sizeEcologyPhenologyDeltaSnowAnatidaeBiologyGeographyArcticReproduction
DOInot available

Abstract

fetched live from OpenAlex

-Nesting ecology of Tundra Swans (Cygnus columbianus columbianus) was studied along the Kashunuk River near Old Chevak (61026'N, 165027'W), on the Yukon-Kuskokwim Delta of western Alaska from 1988-2000. Annual variation in snow-melt chronology, nesting phenology, nesting density, clutch size and nest success was examined. The same area (approximately 23 km2) was searched each year and nests were found as early as possible in the laying period. Laying initiation dates ranged from 1-27 May and hatch dates from 12 June-4July among pairs and years of study. The peak arrival of Tundra Swans and the phenology of nest initiation and hatch were highly correlated with the progression of ice and snow melt in spring. Nest density averaged 0.71 km2 and 89% of nesting pairs hatched at least one egg. Incubation period ranged from 26 to 33 days with a median of 30 days. Clutch size varied significantly among years, driven by a low mean value of 3.4 eggs in 1999. Clutch sizes were generally larger than found in previous investigations on the Yukon-Kuskokwim Delta, and nearly one egg larger than reported for clutches from Alaska's North Slope (=700N). There was no indication of reduced clutch size in years of late spring snow melt, although nesting density tended to be lower.

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 score0.148
Threshold uncertainty score0.294

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 studies0.0010.000
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 head0.021
GPT teacher head0.213
Teacher spread0.192 · 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

Citations9
Published2002
Admission routes1
Has abstractyes

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