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Record W2153968667 · doi:10.14430/arctic687

The Harvest of Beluga Whales in Canada's Western Arctic: Hunter-based Monitoring of the Size and Composition of the Catch

2002· article· en· W2153968667 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueARCTIC · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
Fundersnot available
KeywordsBeluga WhaleBelugaGeographyArcticSex ratioFisheryEstuaryPopulationProductivityOceanographyBiologyDemographyEcology

Abstract

fetched live from OpenAlex

Hunter-based beluga monitoring programs, in place in the Mackenzie Delta since 1973 and in the Paulatuk, Northwest Territories, area since 1989, have resulted in collection of data on the number of whales harvested and on the efficiency of the hunts. Since 1980, data on the standard length, fluke width, sex, and age of the landed whales have also been collected. The number of belugas landed each year averaged 131.8 (SD 26.5, n = 1337) between 1970 and 1979, 124.0 (SD 23.3, n = 1240) between 1980 and 1989, and 111.0 (SD 19.0, n = 1110) between 1990 and 1999. The human population increased during this same period. Removal of belugas from the Beaufort Sea stock, including landed whales taken in the Alaskan harvests, is estimated at 189 per year. The sex ratio of landed belugas from the Mackenzie Estuary was 2.3 males:1 female. Median ages were 23.5 yr (47 growth layer groups [GLG]) for females (n = 80) and 24 yr (48 GLG) for males (n = 286). More than 92% of an aged sample (n = 368) from the harvest consisted of whales 10 or more years old (20 GLG). The rate of removal is small in relation to the expected maximum net productivity rate of this stock. The continued availability of large, old individuals after centuries of harvesting and the apparent lack of change in the size and age structure of the catch in recent years also support a conclusion that the present level of harvest is sustainable.

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.

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 score0.054
Threshold uncertainty score0.148

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 communication0.0000.000
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 head0.015
GPT teacher head0.203
Teacher spread0.188 · 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