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Record W2252780135 · doi:10.1123/mcj.17.1.34

Freely Chosen Cadence During a Covert Manipulation of Ambient Temperature

2013· article· en· W2252780135 on OpenAlex
Geoffrey L. Hartley, Stephen S. Cheung

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMotor Control · 2013
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsBrock University
Fundersnot available
KeywordsCadenceMathematicsAnalysis of varianceAnimal scienceThermal sensationPerceived exertionPhysicsChemistryStatisticsThermodynamicsMedicineInternal medicineBiologyAcoustics

Abstract

fetched live from OpenAlex

The present study investigated relationships between changes in power output (PO) to torque (TOR) or freely chosen cadence (FCC) during thermal loading. Twenty participants cycled at a constant rating of perceived exertion while ambient temperature (Ta) was covertly manipulated at 20-min intervals of 20 °C, 35 °C, and 20 °C. The magnitude responses of PO, FCC and TOR were analyzed using repeated-measures ANOVA, while the temporal correlations were analyzed using Auto-Regressive Integrated Moving Averages (ARIMA). Increases in Ta caused significant thermal strain (p < .01), and subsequently, a decrease in PO and TOR magnitude (p < .01), whereas FCC remained unchanged (p = .51). ARIMA indicates that changes in PO were highly correlated to TOR (stationary r2 = .954, p = .04), while FCC was moderately correlated (stationary r2 = .717, p = .01) to PO. In conclusion, changes in PO are caused by a modulation in TOR, whereas FCC remains unchanged and therefore, unaffected by thermal stressors.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.484
Threshold uncertainty score0.292

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.007
GPT teacher head0.218
Teacher spread0.210 · 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