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Record W2165564778 · doi:10.1139/f08-059

Effect of ambient oxygen on growth and reproduction in Nile tilapia (Oreochromis niloticus)

2008· article· en· W2165564778 on OpenAlexvenueno aff
Jeppe Kolding, Lise Haug, Sigurd O. Stefansson

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNile tilapiaOreochromisGonadosomatic IndexFecundityBiologyContext (archaeology)JuvenileReproductionAnimal scienceTilapiaSexual maturityMaturity (psychological)EcologyFish <Actinopterygii>ZoologyFisheryPopulation

Abstract

fetched live from OpenAlex

Growth, size at maturity, gonadosomatic index (GSI), egg size, and absolute fecundity of Nile tilapia ( Oreochromis niloticus ) were significantly affected by oxygen levels (1.5 ± 1.0, 2.8 ± 1.4, and 6.0 ± 1.8 mg·L–1) in a controlled experiment designed to test the hypothesis (D. Pauly. 1984. J. Cons. Int. Explor. Mer, 41: 280–284) that O2 is the controlling factor for the transition from juvenile to adult in fish, in general, in the context of phenotypic life history plasticity and “stunting” in tilapias. Size at maturity and the estimated asymptotic size decreased with decreasing O2 concentration, as predicted by Pauly’s hypothesis. All fish matured at the same age (18 weeks old), which is in contrast to conventional definitions of stunting. This finding challenges the suggested plasticity in age at first maturity for tilapia. The results also challenge the hypothesis that stunting is a unique recruitment mechanism, as the smaller fish in the group with low oxygen concentration produced smaller and fewer eggs than the larger fish in the group with high oxygen concentration.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

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)0.0000.000

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 head0.010
GPT teacher head0.197
Teacher spread0.187 · 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

Citations65
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicFish Ecology and Management Studies→French-language works237,207→