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Record W2467368894 · doi:10.1139/cjfas-2015-0600

Changes in body size of Canadian Pacific salmon over six decades

2016· article· en· W2467368894 on OpenAlexafffundvenueabout
Kyla M. Jeffrey, Isabelle M. Côté, James R. Irvine, John D. Reynolds

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsFisheries and Oceans CanadaSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaPacific Salmon FoundationLeading Edge Endowment Fund
KeywordsOncorhynchusChinook windPacific decadal oscillationFisheryBiologyBiomass (ecology)Pacific oceanPredationOcean gyreEnvironmental scienceEcologyFish <Actinopterygii>OceanographySubtropics

Abstract

fetched live from OpenAlex

Body size can sometimes change rapidly as an evolutionary response to selection or as a phenotypic response to changes in environmental conditions. Here, we revisit a classic case of rapid change in body size of five species of Pacific salmon (Oncorhynchus spp.) caught in Canadian waters, with a six-decade analysis (1951–2012). Declines in size at maturity of up to 3 kg in Chinook (Oncorhynchus tshawytscha) and 1 kg in coho salmon (Oncorhynchus kisutch) during the 1950s and 1960s were later reversed to match or exceed earlier sizes. In contrast, there has been little change in sockeye salmon (Oncorhynchus nerka) sizes and initial declines in pink (Oncorhynchus gorbuscha) and chum salmon (Oncorhynchus keta) sizes have halted. Biomass of competing salmon species contributed to changes in size of all five species, and ocean conditions, as reflected by the North Pacific Gyre Oscillation and the Multivariate ENSO (El Niño – Southern Oscillation) indices, explained variation in four of the species. While we have identified a role of climate and density dependence in driving salmon body size, any additional influence of fisheries remains unclear.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.026
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.014
GPT teacher head0.204
Teacher spread0.190 · 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

Citations49
Published2016
Admission routes4
Has abstractyes

Explore more

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