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Record W2790437684 · doi:10.1002/jez.2145

Comparability and repeatability of three commonly used methods for measuring endurance capacity

2017· article· en· W2790437684 on OpenAlexfundno aff
James Baxter‐Gilbert, Max Mühlenhaupt, Martin J. Whiting

Bibliographic record

VenueJournal of Experimental Zoology Part A Ecological and Integrative Physiology · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNational Park ServiceUniversity of New South WalesMacquarie University
KeywordsRepeatabilityComparabilityEndurance trainingTreadmillVO2 maxRange (aeronautics)Cardiorespiratory fitnessComputer sciencePhysical medicine and rehabilitationStatisticsPhysical therapyMedicineMathematicsEngineering

Abstract

fetched live from OpenAlex

Measures of endurance (time to exhaustion) have been used to address a wide range of questions in ecomorphological and physiological research, as well as being used as a proxy for survival and fitness. Swimming, stationary (circular) track running, and treadmill running are all commonly used methods for measuring endurance. Despite the use of these methods across a broad range of taxa, how comparable these methods are to one another, and whether they are biologically relevant, is rarely examined. We used Australian water dragons (Intellagama lesueurii), a species that is morphologically adept at climbing, swimming, and running, to compare these three methods of endurance and examined if there is repeatability within and between trial methods. We found that time to exhaustion was not highly repeatable within a method, suggesting that single measures or a mean time to exhaustion across trials are not appropriate. Furthermore, we compared mean maximal endurance times among the three methods, and found that the two running methods (i.e., stationary track and treadmill) were similar, but swimming was distinctly different, resulting in lower mean maximal endurance times. Finally, an individual's endurance rank was not repeatable across methods, suggesting that the three endurance trial methods are not providing similar information about an individual's performance capacity. Overall, these results highlight the need to carefully match a measure of performance capacity with the study species and the research questions being asked so that the methods being used are behaviorally, ecologically, and physiologically relevant.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.106
GPT teacher head0.354
Teacher spread0.248 · 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 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

Citations7
Published2017
Admission routes1
Has abstractyes

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