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Record W2952906663 · doi:10.1201/9780429025303-9

Legacy and Emerging Pollutants in Marine Mammals’ Habitat from British Columbia, Canada: Management perspectives for sensitive marine ecosystems

2019· book-chapter· en· W2952906663 on OpenAlexaboutno aff
Juan José Alava

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
Fundersnot available
KeywordsMarine ecosystemHabitatEcosystemGeographyPollutantEcologyEnvironmental scienceEnvironmental resource managementOceanographyFisheryBiologyGeology

Abstract

fetched live from OpenAlex

The Canadian west coast is recognized for the wide diversity of marine habitats such as long, deep fjords and channels, protected coastal seas, outer continental shelf areas with submarine canyons and offshore pelagic waters. The marine environment of British Columbia (BC) is home to 31 species of marine mammals of which 25, 5 and 1 are cetaceans, pinnipeds and mustelid, respectively. Oil pipeline projects in the BC coastal-marine region cannot be ruled out as potential threats as either a direct impact from coastal-based infrastructural operations or maritime traffic of tankers for marine mammals and their habitats. Impact assessment and source control programs have received little attention and need to be in place to ensure the protection of marine mammals in coastal BC. Harbour porpoises are one of the smallest cetaceans and coastal inhabitants residing in shallow waters, and commonly distributed throughout BC waters, including the southern straits, mainland inlets and Queen Charlotte Basin, but showing low densities in deep-waters.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.007
Science and technology studies0.0030.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.002

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 head0.008
GPT teacher head0.188
Teacher spread0.180 · 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

Citations8
Published2019
Admission routes1
Has abstractyes

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