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Record W2014214308 · doi:10.1002/oa.610

Regional variability in Mackenzie Inuit beluga whale use

2002· article· en· W2014214308 on OpenAlexafffundabout
T. Max Friesen, David Morrison

Bibliographic record

VenueInternational Journal of Osteoarchaeology · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsMusée de la CivilisationUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBelugaBeluga WhaleGeographyFisheryWhalingWhaleRange (aeronautics)LeucasSubsistence agricultureOceanographyArcticGeologyArchaeologyBiologyAgriculture

Abstract

fetched live from OpenAlex

Abstract Inuit of the Mackenzie Delta region, Northwest Territories, relied on a wide range of subsistence resources, however they are best known as the consummate hunters of beluga whales (Delphinapterus leucas). This species represented a focal resource for the two regional groups centred on the East Channel of the Mackenzie River, but was available much less frequently and reliably to adjacent groups, who relied to a greater degree on alternative resources such as caribou, fish, seals, and bowhead whales. In this paper, we compare archaeofaunas from sites located in the “core” beluga whaling zone of the Mackenzie River East Channel with other sites to the east and west for which direct access to beluga whales was either reduced or non‐existent. Bone frequencies are compared both in terms of proportional species representation in site archaeofaunas, and in terms of differential element representation. These comparisons are then interpreted within a framework emphasizing regional economic patterns, as well as local variability in patterns of beluga acquisition, storage, transport, and disposal. Copyright © 2002 John Wiley & Sons, Ltd.

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)0.001
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 score0.852
Threshold uncertainty score0.294

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.036
GPT teacher head0.264
Teacher spread0.228 · 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

Citations5
Published2002
Admission routes3
Has abstractyes

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