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The effect of temperature and acclimation period on repeat swimming performance in cutthroat trout

2004· article· en· W1974387683 on OpenAlexaff
Meaghan J. MacNutt, S. G. Hinch, Anthony P. Farrell, Stephanie M. Topp

Bibliographic record

VenueJournal of Fish Biology · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia
Fundersnot available
KeywordsAcclimatizationBiologyTroutHatcheryOncorhynchusAnimal scienceEcologyFisheryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Hatchery cutthroat trout Oncorhynchus clarki clarki were used to examine the effects of 48 h and 3 week temperature acclimation periods on critical swimming speed (Ucrit). The Ucrit was determined for fish at acclimation temperatures of 7, 14 and 18° C using two consecutive ramp‐Ucrit tests in mobile Brett‐type swim tunnels. An additional group was tested at the stock's ambient rearing temperature of 10° C. The length of the temperature acclimation period had no significant effect on either the first or the second Ucrit(Ucrit‐1 and Ucrit‐2, respectively) or on the recovery ratio (the quotient of Ucrit‐2 Ucrit‐1−1). As anticipated, there was a significant positive relationship between Ucrit‐1 and temperature (P < 0·01) for both acclimation periods, and an increasing, though non‐significant, trend between Ucrit‐2 and temperature (P = 0·10). Acclimation temperature had no significant effect (P = 0·71) on the recovery ratio. These results indicate that a 48 h acclimation to experimental temperatures within the range of −3 to +8° C of the acclimation temperature may be sufficient in studies of swimming performance with this species. This ability to acclimate rapidly is probably adaptive for cutthroat trout and other species that occupy thermally variable environments.

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)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.004
GPT teacher head0.216
Teacher spread0.213 · 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

Citations83
Published2004
Admission routes1
Has abstractyes

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