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Record W2105420076 · doi:10.1093/icesjms/fsp267

Changes in the reproductive parameters of female harp seals (Pagophilus groenlandicus) in the Northwest Atlantic

2009· article· en· W2105420076 on OpenAlexaff
Becky Sjare, Garry B. Stenson

Bibliographic record

VenueICES Journal of Marine Science · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsSexual maturityHARPPopulationBiologyFisheryGeographyEcologyDemography

Abstract

fetched live from OpenAlex

Abstract Sjare, B., and Stenson, G. B. 2010. Changes in the reproductive parameters of female harp seals (Pagophilus groenlandicus) in the Northwest Atlantic. – ICES Journal of Marine Science, 67: 304–315. Changes in female harp seal (Pagophilus groenlandicus) reproductive parameters from 1980 to 2004, and long-term trends since the early 1950s, are evaluated. Estimates of the total number of seals in the Northwest Atlantic declined from ∼3.0 million in the 1950s to 1.8 million in the early 1970s, then increased steadily to 5.5 million in 1996, at which relatively stable level it has remained since. Pregnancy rates increased from ∼86% in the 1950s to a high of 98% in the mid-1960s, then declined to ∼65–70% by the early 1990s; the rate then varied between 45 and 70% from 2000 to 2004. Concurrently, the mean age at sexual maturity decreased from 5.8 (s.e = 0.02) years in the mid-1950s to 4.1 (s.e. = 0.02) in the late 1970s, increased to 5.5 (s.e. = 0.03) years by the early 1990s, and peaked at 5.7 (s.e. = 0.01) in 1995. From 2000 to 2004, mean age varied from 4.9 (s.e. = 0.01) to 6.0 (s.e. = 0.01) years. Although the direction of change in each of the parameters was consistent with a density-dependent response, changes in population size explained relatively little of the variability observed, suggesting that other ecological or environmental factors were influential.

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 score0.033
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.026
GPT teacher head0.265
Teacher spread0.240 · 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

Citations17
Published2009
Admission routes1
Has abstractyes

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