MétaCan
Menu
← Back to cohort
Record W4313621147 · doi:10.3389/fpsyg.2022.934308

How physical activity and passion color the passage of time: A response with ultra-trail runners

2023· article· en· W4313621147 on OpenAlexaff
Quentin Hallez, Marine Paucsik, Guillaume Tachon, Rébecca Shankland, Fanny Marteau-Chasserieau, Mathilde Plard

Bibliographic record

VenueFrontiers in Psychology · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPassionPsychologyHappinessFeelingContext (archaeology)PerceptionSocial psychology

Abstract

fetched live from OpenAlex

The aim of this study was to replicate the results of a lengthening effect caused by physical activity already observed in duration length judgment, using the time passage judgment measure, while exploring the effects of passion types (obsessive vs. harmonious) on time perception. A total of 378 ultra-trail runners responded to an online questionnaire in which the type of passion and the passage of time (PoT) judgments associated with both an ultra-trail context and a non-trail daily context were collected. The results showed that participants systematically judged the time as being dilated in a situation of sports practice, thus extending the results obtained in interval duration judgment studies. This study also showed an influence of the type of passion: higher levels of harmonious passion were related to greater feelings of time dilation, while higher levels of obsessive passion were related to greater feelings of both time contraction and time dilation. Results are discussed in light of the two major factors that influence the PoT referenced in the literature, namely, attention and happiness level.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
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)0.0020.000

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 head0.028
GPT teacher head0.311
Teacher spread0.283 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in Psychology→Same topicNeuroscience and Music Perception→French-language works237,207→