MétaCan
Menu
Back to cohort
Record W3011624103 · doi:10.14430/arctic70035

Observations of Annual Walrus (<i>Odobenus rosmarus divergens</i>) Migrations in the Nearshore Waters of the Chukotka Peninsula from 1990 to 2012

2020· article· en· W3011624103 on OpenAlexvenueno aff
Vladimir V. Melnikov

Bibliographic record

VenueARCTIC · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
Fundersnot available
KeywordsPeninsulaOceanographySubmarine pipelineGeographyFisheryAerial surveyAbundance (ecology)GeologyArchaeologyBiology

Abstract

fetched live from OpenAlex

After the end of the commercial harvest, research regarding the Pacific walrus (Odobenus rosmarus divergens) in Russia was reduced and focused on the observation of animals at land-based haul-outs. This paper presents the long-term observations of the distribution, relative abundance, and direction of seasonal movements of walruses in the offshore waters of the Chukotka Peninsula, based on data obtained in 1990 – 2012. Observations of Pacific walruses and other marine mammals were conducted mainly from April through November, but some were conducted all year round. In some years up to 30 Native Chukotkan observers were employed at this task. Some watched from observation posts in Native villages onshore, and others from motorboats during hunting trips. These observations have shown that walruses are rare in January and February in the nearshore waters of the Chukotka Peninsula. Their numbers begin to increase in March. The northward movement of walruses begins in April, and walruses migrate from the Bering Sea to the Chukchi Sea throughout the summer months and early autumn. Based on observations from posts located directly in front of the southern Bering Strait, I conclude that 106 – 1055 walruses pass through the Bering Strait from July to September, to the northwest and north. At the haul-outs in the Gulf of Anadyr, the relative number of walruses remains stable during the summer (up to 11 000 individuals at all haul-outs in total based on observers’ estimates) and decreases only with the appearance of ice in October – November.

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 score0.128
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.028
GPT teacher head0.219
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 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueARCTICSame topicMarine animal studies overviewFrench-language works237,207