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Record W2149841276 · doi:10.1139/f09-132

Temporal trends in probabilistic maturation reaction norms and growth of Atlantic cod (Gadus morhua) on the Icelandic shelf

2009· article· en· W2149841276 on OpenAlexvenueno aff
Heidi Pardoe, Anssi Vainikka, Gudmundur Thórdarson, Guðrún Marteinsdóttir, Mikko Heino

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsGadusFishingAtlantic codGadidaeBiologySexual maturityJuvenileFisheryEcologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Decreasing temporal trends in probabilistic maturation reaction norm (PMRN) midpoints, symptomatic of earlier maturation despite environmentally induced variation in growth, have been observed in many exploited fish stocks. Here, we studied the growth and maturation trends of female and male Icelandic cod ( Gadus morhua ) by estimating PMRN midpoints for cohorts 1964–1999 and found evidence that a shift towards maturation at smaller sizes and younger ages has occurred independently of changes in growth, condition, and temperature. Weighting the data with regional survey abundance estimates to account for spatial heterogeneity in maturity status and sampling intensity did not qualitatively affect the temporal trends. Length-at-age also decreased through the study period, which, through simulations, could be attributed to the energetic costs of earlier maturity at maturing age groups but not at younger ages. These findings support the hypothesis that such changes in maturation schedules are not caused by environmental factors alone but could also reflect a genetic change, potentially in response to intensive fishing.

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 score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.020
GPT teacher head0.228
Teacher spread0.208 · 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

Citations33
Published2009
Admission routes1
Has abstractyes

Explore more

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