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Record W2169931891 · doi:10.1098/rstb.2007.2111

Cardiorespiratory performance during prolonged swimming tests with salmonids: a perspective on temperature effects and potential analytical pitfalls

2007· review· en· W2169931891 on OpenAlexaff
Anthony P. Farrell

Bibliographic record

VenuePhilosophical Transactions of the Royal Society B Biological Sciences · 2007
Typereview
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRespirometerCardiorespiratory fitnessRespirometryEnvironmental scienceRacewayRespirationOxygenVO2 maxBiologyChemistryPhysiologyHeart rateMedicineAnatomyThermodynamicsPhysicsInternal medicine

Abstract

fetched live from OpenAlex

A prolonged swimming trial is the most common approach in studying steady-state changes in oxygen uptake, cardiac output and tissue oxygen extraction as a function of swimming speed in salmonids. The data generated by these sorts of studies are used here to support the idea that a maximum oxygen uptake is reached during a critical swimming speed test. Maximum oxygen uptake has a temperature optimum. Potential explanations are advanced to explain why maximum aerobic performance falls off at high temperature. The valuable information provided by critical swimming tests can be confounded by non-steady-state swimming behaviours, which typically occur with increasing frequency as salmonids approach fatigue. Two major concerns are noted. Foremost, measurements of oxygen uptake during swimming can considerably underestimate the true cost of transport near critical swimming speed, apparently in a temperature-dependent manner. Second, based on a comparison with voluntary swimming ascents in a raceway, forced swimming trials in a swim tunnel respirometer may underestimate critical swimming speed, possibly because fish in a swim tunnel respirometer are unable to sustain a ground speed.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.839
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.034
GPT teacher head0.280
Teacher spread0.246 · 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 teacher head, not a consensus.

Study designOther design
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

Citations151
Published2007
Admission routes1
Has abstractyes

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