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Record W2964896276 · doi:10.1139/cjfas-2019-0033

Otolith growth and zone formation during first maturity and spawning of Atlantic cod (<i>Gadus morhua</i>)

2019· article· en· W2964896276 on OpenAlexvenueno aff
Christian Irgens, Arild Folkvord, Håkon Otterå, Olav Sigurd Kjesbu

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
FundersNorges Forskningsråd
KeywordsGadusOtolithSexual maturityAtlantic codGadidaeFisheryBiologyFecundityReproductionStock (firearms)EcologyGeographyFish <Actinopterygii>Population

Abstract

fetched live from OpenAlex

Specific impacts of somatic growth, sexual maturation, and spawning events on otolith zone formation in Atlantic cod (Gadus morhua) were assessed in a 33-month tank experiment, using Barents Sea cod and Norwegian coastal cod. High and low feeding ration combinations were used to mimic environmental stressors in the field. For both stocks, apparent macrostructural “spawning zones” in otoliths are registered in statutory stock monitoring programs to estimate age at maturity, thus adding key information to stock biomass assessments. We found that substantial energy investments in reproduction caused reductions in otolith growth and altered proportional width between translucent and opaque zones. These effects, however, were only statistically significant among individuals with high reproductive investments, while otoliths from individuals with low investments did not differ from the otoliths for immatures. Reproduction may thus not necessarily induce spawning zones, and alternatively, spawning zones may not necessarily reflect reproduction. Altogether, this suggests that the individual energy level, as a premise for metabolic activity, plays a key role in the formation of such zones and thus is related to environmental conditions.

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)0.000
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 score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.010
GPT teacher head0.194
Teacher spread0.184 · 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

Citations15
Published2019
Admission routes1
Has abstractyes

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