MétaCan
Menu
Back to cohort
Record W2145280532 · doi:10.14430/arctic367

Offshore Distances of Bowhead Whales (<i>Balaena mysticetus</i>) Observed during Fall in the Beaufort Sea, 1982–2000: An Alternative Interpretation

2009· article· en· W2145280532 on OpenAlexvenueno aff
Stephen D. Treacy, Jeffrey S. Gleason, Cleveland J. Cowles

Bibliographic record

VenueARCTIC · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
Fundersnot available
KeywordsOceanographySea iceWhaleArctic ice packTransectFisheryEnvironmental scienceGeologyGeographyBiology

Abstract

fetched live from OpenAlex

Nineteen years (1982– 2000) of sighting data from fall aerial surveys of bowhead whales (Balaena mysticetus) in the Alaskan Beaufort Sea were analyzed to determine how patterns in the distribution of migrating bowhead whales relate to annual sea-ice conditions. Transect sighting rate (transect sightings/km) indicated (ANOVA; F2, 980 = 143.84, p < 0.0001) that bowhead whales occurred farther offshore in years of heavy ice conditions (73.4 km, 95% CL: 67.2–79.6 km) than in years of moderate (49.3 km, 95% CL: 44.8–53.84 km), or light (31.2 km, 95% CL: 30.0–32.4 km) ice conditions. The most plausible explanation for the observed pattern in bowhead whale distribution is that in years of heavy ice conditions (annual pack ice; 1983, 1988, 1991), the developing landfast ice limits availability of shallow nearshore habitat, thus necessitating use of leads and ice openings in deeper water. We acknowledge that factors such as bathymetry, ocean currents, transport, and food availability may also interact to influence autumn distribution of bowhead whales. In heavy ice years, however, these factors likely exert less influence on bowhead whale distribution than in years with light to moderate ice conditions.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.924

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 communication0.0000.001
Open science0.0010.000
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 head0.020
GPT teacher head0.247
Teacher spread0.226 · 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 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
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueARCTICSame topicMarine animal studies overviewFrench-language works237,207