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Record W2169729957 · doi:10.1139/f01-078

Predictions of critical habitat for five whale species in the waters of coastal British Columbia

2001· article· en· W2169729957 on OpenAlexfundvenueaboutno aff
Edward J. Gregr, Andrew W. Trites

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaNational Academy of Sciences of Ukraine
KeywordsSperm whaleWhalingFisheryHabitatHumpback whaleOceanographyWhaleBalaenopteraGeographyCetaceaBathymetryEstuaryEnvironmental scienceEcologyBiologyGeology

Abstract

fetched live from OpenAlex

Whaling records from British Columbia coastal whaling stations reliably report the positions of 9592 whales killed between 1948 and 1967. We used this positional information and oceanographic data (bathymetry, temperature, and salinity) to predict critical habitat off the coast of British Columbia for sperm (Physeter macrocephalus), sei (Balaenoptera borealis), fin (Balaenoptera physalus), humpback (Megaptera novaeangliae), and blue (Balaenoptera musculus) whales. We used generalized linear models at annual and monthly time scales to relate whale occurrence to six predictor variables (month, depth, slope, depth class, and sea surface temperature and salinity). The models showed critical habitat for sei, fin, and male sperm whales along the continental slope and over a large area off the northwest coast of Vancouver Island. Habitat models for blue, humpback, and female sperm whales were relatively insensitive to the predictor variables, owing partially to the smaller sample sizes for these groups. The habitat predictions lend support to recent hypotheses about sperm whale breeding off British Columbia and identify humpback whale habitat in sheltered bays and straits throughout the coast. The habitat models also provide insights about the nature of the linkages between the environment and the distribution of whales in the North Pacific Ocean.

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 score0.680
Threshold uncertainty score0.748

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 studies0.0000.002
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 head0.023
GPT teacher head0.222
Teacher spread0.200 · 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

Citations138
Published2001
Admission routes3
Has abstractyes

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