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Record W2120318456 · doi:10.1242/jeb.01057

Cardiac plasticity in fishes: environmental influences and intraspecific differences

2004· review· en· W2120318456 on OpenAlexaff
A. Kurt Gamperl, Anthony P. Farrell

Bibliographic record

VenueJournal of Experimental Biology · 2004
Typereview
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsSimon Fraser UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsBiologyHypoxia (environmental)Intraspecific competitionCardiovascular physiologyFish physiologyPhysiologyFish <Actinopterygii>ZoologyEndocrinologyFisheryChemistry

Abstract

fetched live from OpenAlex

Fish cardiac physiology and anatomy show a multiplicity of intraspecific modifications when exposed to prolonged changes in environmentally relevant parameters such as temperature, hypoxia and food availability, and when meeting the increased demands associated with training/increased activity and sexual maturation. Further, there is evidence that rearing fish under intensive aquaculture conditions significantly alters some, but not all, aspects of cardiac anatomy and physiology. This review focuses on the responses of cardiac physiology and anatomy to these challenges, highlighting where applicable, the importance of hyperplastic (i.e. the production of new cells) vs hypertrophic (the enlargement of existing cells) growth to the adaptive response of the heart. In addition, we summarize recent studies that have explored the relationship between the myocardial protection afforded by preconditioning and myocardial hypoxia tolerance. This latter research clearly demonstrates the capacity of the fish heart to adjust to short-term perturbations, and shows that it can be difficult to predict how short-term and long-term alterations in cardiac physiology will interact.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.036
GPT teacher head0.287
Teacher spread0.251 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations282
Published2004
Admission routes1
Has abstractyes

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