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Record W3143653869 · doi:10.33997/j.afs.2021.34.1.002

The Relationship Between Size at Maturity and Maximum Size in Cichlid Populations Corroborates the Gill-Oxygen Limitation Theory (GOLT)

2021· article· en· W3143653869 on OpenAlexaff
U.S. Amarasinghe, Daniel Pauly

Bibliographic record

VenueAsian Fisheries Science · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSpawn (biology)CichlidBiologyTilapiaFisheryAquacultureFish <Actinopterygii>EcologyZoology

Abstract

fetched live from OpenAlex

Fish generally mature at a smaller fraction of their maximum sizes than birds and mammals. The farmed tilapia (Family Cichlidae) can tolerate adverse conditions that result in stunting and which also cause the fish to spawn at small size. Such spawning at small size (or ‘early spawning’) is usually perceived as a unique feature of tilapia. The mechanism that explains how stressful environmental conditions tend to reduce the maximum size that fish can reach is very general and should apply to all fish. However, not all fish species are equally hardy, and most fish do not survive in the stunted or dwarf form under stressful environmental conditions. Tilapia, and other cichlids, on the other hand, can handle stressful conditions, if by remaining stunted. The present study shows that tilapia and other cichlids do not spawn ‘earlier’ than other teleosts. Rather, they are exceptionally tolerant of stressful environmental conditions, but with elevated metabolism. By reducing their growth and the maximum size they can reach ‘stunting’, they also reduce the sizes at which their maturity is initiated (‘early spawning’). This corroborates the gill-oxygen limitation theory (GOLT), which identifies spawning as an event rather than a determinant of fish growth.

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)0.003
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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)0.0030.000

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 head0.028
GPT teacher head0.246
Teacher spread0.218 · 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

Citations18
Published2021
Admission routes1
Has abstractyes

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