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Record W3012844094

Menthol Mouth Rinsing Improves Cycling Performance in Females under Heat Stress

2019· dissertation· en· W3012844094 on OpenAlexfundno aff
Erica H. Gavel

Bibliographic record

VenueTSpace · 2019
Typedissertation
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsnot available
FundersUniversity of TorontoUniversity of Ontario Institute of Technology
KeywordsMentholCyclingStress (linguistics)Heat stressMaterials scienceDentistryMedicineChemistryAnimal scienceBiologyGeography
DOInot available

Abstract

fetched live from OpenAlex

This study investigated the effects of a menthol mouth rinse on performance and physiological responses in female cycling athletes during a 30-km individual time trial (ITT). Participants (n=9) cycled for 30-km in hot conditions (30 ± 0.6 °C, 70 ± 1% relative humidity, 12 ± 1 km/h windspeed) on two test occasions using a menthol (MEN) mouth rinse (MR) occurring every 5-km. Perceptual responses (perceived exertion and thermal perception) were recorded at 5, 10, 15, 20, 25, and 30-km. The MEN MR significantly improved ITT performance by 2.3 ± 2.7% relative to PLA (p= 0.034, d= 0.85, 95% CI= 8.43 to 166.9). There were no significant differences in perceived exertion and thermal perception. These results demonstrate that a non-thermal cooling agent can improve physiological performance in moderately trained female cyclists with no change in perceived exertion or thermal perception.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.866
Threshold uncertainty score0.779

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.044
GPT teacher head0.379
Teacher spread0.335 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2019
Admission routes1
Has abstractyes

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