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Record W2039925914 · doi:10.1139/z00-045

Satellite-monitored movements of radio-tagged bowhead whales in the Beaufort and Chukchi seas during the late-summer feeding season and fall migration

2000· article· en· W2039925914 on OpenAlexvenueaboutno aff
Bruce R. Mate, Gregory K. Krutzikowsky, Martha H. Winsor

Bibliographic record

VenueCanadian Journal of Zoology · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
Fundersnot available
KeywordsBeaufort scaleWhaleOceanographyBeaufort seaBayBeluga WhaleRight whaleCetaceaGeographyGeologyFisherySea iceArcticBiology

Abstract

fetched live from OpenAlex

From 30 August to 6 September 1992, we tagged 12 juvenile bowhead whales (Balaena mysticetus) with Argos satellite-monitored radio tags in the Canadian Beaufort Sea off the Mackenzie River Delta. Eight tags documented [Formula: see text]9820 km of movements between 392 locations during 111 whale-tracking days. The whales did not move in unison. Individual movements and average speeds (1.1-5.8 km/h) varied widely. One whale stayed in Mackenzie Bay for 23.5 d, while the rest stayed an average of only 2.4 d. The majority of locations for all whales were in shallow water: 65% at <50 m depth and 87% at <100 m depth. Seven whales went into water >100 m deep and four were in water >500 m deep. The whale with the longest record traveled [Formula: see text]3886 km to Siberia in 32.5 d, averaging 5.0 km/h. Its westerly route through the Beaufort and Chukchi seas was between 70° and 72°N and primarily in heavy ice ([Formula: see text]90% coverage), which was continuous west of 151°W. This whale's speed was faster, though not significantly, in heavy ice than in more open water. This is the first detailed documentation of the route and speed of a bowhead whale during its fall migration from Canadian to Russian waters.

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 score0.447
Threshold uncertainty score0.889

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.012
GPT teacher head0.214
Teacher spread0.202 · 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

Citations67
Published2000
Admission routes2
Has abstractyes

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