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Insights into the population structure of blue whales in the Eastern North Pacific from recent sightings and photographic identification

2009· article· en· W1989242722 on OpenAlexaff
John Calambokidis, Jay Barlow, John K. B. Ford, Todd E. Chandler, Annie B. Douglas

Bibliographic record

VenueMarine Mammal Science · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsFisheries and Oceans Canada
FundersSouthwest Fisheries Science CenterNational Oceanic and Atmospheric Administration
KeywordsWhalingWhalePopulationGeographyFisheryOceanographyCetaceaPredationEcologyArchaeologyBiologyGeologyDemography

Abstract

fetched live from OpenAlex

Abstract Blue whales were widely distributed in the North Pacific prior to the primary period of modern commercial whaling in the early 1900s. Despite concentrations of blue whale catches off British Columbia and in the Gulf of Alaska, there had been few documented sightings in these areas since whaling for blue whales ended in 1965. In contrast, large concentrations of blue whales have been documented off California and Baja California and in the eastern tropical Pacific since the 1970s, but it was not known if these animals were part of the same population that previously ranged into Alaskan waters. We document 15 blue whale sightings off British Columbia and in the Gulf of Alaska made since 1997, and use identification photographs to show that whales in these areas are currently part of the California feeding population. We speculate that this may represent a return to a migration pattern that has existed for earlier periods for eastern North Pacific blue whale population. One possible explanation for a shift in blue whale use is changes in prey driven by changes in oceanographic conditions, including the Pacific Decadal Oscillation (PDO), which coincides with some of the observed shifts in blue whale occurrence.

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 score0.135
Threshold uncertainty score0.269

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 communication0.0000.000
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 head0.009
GPT teacher head0.215
Teacher spread0.206 · 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

Citations100
Published2009
Admission routes1
Has abstractyes

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