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Record W2589267665 · doi:10.1080/0361073x.2017.1276378

Aging and Half-Ironman Performance

2017· article· en· W2589267665 on OpenAlex

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

VenueExperimental Aging Research · 2017
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsLakehead University
FundersNational Institute on Aging
KeywordsContext (archaeology)CohortDemographyChampionshipCyclingLongitudinal studyGerontologyMedicineGeography

Abstract

fetched live from OpenAlex

Background/Study Context: Previous research on triathlon performance analyzed age trends for the Top Ten or Top Five finishers in world championship or national races at Olympic, Half-Ironman, and Ironman distances. The findings indicated higher age declines and/or earlier onset of decline in swimming and running than cycling. However, the designs of those studies took no account of possible differences between cross-sectional and longitudinal trends (i.e., cohort differences versus age changes). METHODS: This study analyzed performance times over the inaugural 5 years of the Half-Ironman world championship held in Clearwater, Florida, from 2006 to 2010. Only one previous study is known that examined age trends in performance for this triathlon distance. The data from the official race results showed 5549 age class competitors that provided 6541 sets of observations. Analyses by mixed linear modeling (MLM) partitioned the data to compare discrete and interactive cross-sectional and longitudinal trends for swimming, cycling, and running, respectively. RESULTS: The findings showed an historical decrease in cycling and running but not swimming times. Performance times were lower by men than women, with the gender discrepancy higher in some older age classes. Comparable to earlier findings for the Half-Ironman triathlon, cross-sectional performance decline was apparent for all triathlon activities from an early cohort age (i.e., 35-39 years). Although longitudinal trend showed significant gains for swimming, running, and overall times, interactions between cohort age and age change showed longitudinal decline that began at a younger cohort age for running (35-39 years) than swimming (50-55 years), but the interaction was nonsignificant for cycling. These interactions add to the knowledge about cohort differences and age changes in triathlon performance. CONCLUSIONS: Practical applications of the findings suggest that conservation of effort might explain the absence of longitudinal change in cycling performance at older cohort ages. The authors reason that increased effort in cycling might benefit overall times of older triathletes.

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)0.001
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 score0.202
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.134
GPT teacher head0.459
Teacher spread0.325 · 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