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Record W1965151099 · doi:10.7557/3.2684

Status of harbour seals (<i>Phoca vitulina</i>) in Atlantic Canada

2010· article· en· W1965151099 on OpenAlexaffabout
Mike O. Hammill, W. Don Bowen, Becky Sjare

Bibliographic record

VenueNAMMCO Scientific Publications · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans Canada
Fundersnot available
KeywordsPhocaHarbourFisheryGeographyPopulationBayHabitatSubspeciesSubsistence agricultureEcologyBiologyArchaeologyAgriculture

Abstract

fetched live from OpenAlex

Harbour seals are associated with small islets, reefs and rocks exposed at low tide and estuarine habitats throughout eastern Canada. Evidence of harvesting by indigenous people has been found in pre-European contact archaeological excavations. A bounty harvest as well as subsistence and commercial hunting probably lead to a decline in the population from 1949 to the early 1970s. The bounty was removed in 1976, and harbour seals, in the southern parts of their range have been protected since then. There is little information available on total abundance and current population trend. Mitochondrial and microsatellite DNA research has shown separation between Northeast and Northwest Atlantic harbour seals. Within Canada, the subspecies Phoca vitulina concolor shows some population sub-structure with three distinct units that could be separated into Hudson Bay, Gulf of St. Lawrence and Sable Island. Urban development resulting in habitat degradation is probably the most important factor affecting harbour seal populations in AtlanticCanada, although other factors such as incidental catches in commercial fisheries and competition with grey seals may also be important.

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 score0.035
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.237
Teacher spread0.223 · 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

Citations14
Published2010
Admission routes2
Has abstractyes

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