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Latitudinal variation in fecundity among Arctic charr populations in eastern North America

2005· article· en· W2009605454 on OpenAlexaffabout
Michael Power, J. Brian Dempson, James D. Reist, Carl J. Schwarz, G. Power

Bibliographic record

VenueJournal of Fish Biology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsConestoga CollegeSimon Fraser UniversityFisheries and Oceans CanadaUniversity of Waterloo
Fundersnot available
KeywordsFecundityBiologyCline (biology)ArcticEcologySalvelinusLatitudeRange (aeronautics)Fish migrationHabitatZoologyPopulationFisheryFish <Actinopterygii>GeographyDemographyTrout

Abstract

fetched live from OpenAlex

Variation in fecundity was examined from 32 populations of Arctic charrSalvelinus alpinusin eastern North America covering a range of 37° latitude and extending from Maine, U.S.A., to northern Ellesmere Island in the Canadian Arctic. Populations were classed as dwarf, normal or anadromous and covered a suite of different habitat and climatic regimes. Fecundity varied with fork length (LF), withLFadjusted fecundity differing significantly among populations within each of the morphotypes implying that fecundity was a continuously responsive trait influenced by local environmental factors. Latitudinal variation in fecundity was also evident among morphotypes when the simultaneous effects of both latitude andLFwere controlled. There was a significant trade‐off between fecundity and egg size in two of five populations of anadromous Arctic charr, but no evidence in limited data from either normal or dwarf populations. In contrast with some other studies of fecundity in salmonids, there was no evidence for a latitudinal cline in egg size.

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)0.001
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 score0.938
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

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

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 head0.259
Teacher spread0.236 · 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

Citations63
Published2005
Admission routes2
Has abstractyes

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