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Record W7019857770

Indices Of Airway Function In In-Season Collegiate Swimmers Over Eight Weeks

2018· other· en· W7019857770 on OpenAlexfundno aff

Bibliographic record

VenueNC Digital Online Collection of Knowledge and Scholarship (The University of North Carolina at Greensboro) · 2018
Typeother
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsnot available
FundersQueen's University
KeywordsPulmonary function testingBronchoconstrictionAirwaySpirometryAsthmaRepeated measures design
DOInot available

Abstract

fetched live from OpenAlex

The repeated exposure to disinfectant by-products in swimming pool environments may worsen pulmonary function and contribute to symptoms of exercise induced bronchoconstriction (EIB) in swimmers. The purpose of this study was to comprehensively examine whether spirometric indicators of pulmonary function change over an indoor swim season in competitive collegiate swimmers and to perform a pilot investigation on the efficacy of fish-oil supplementation in swimmers with EIB over the course of 8 weeks. Competitive swimmers (n=13, 18-25 years of age) were recruited for participation in the study. Swimmers underwent pulmonary function and submaximal exercise testing before and after an eight-week period. Pulmonary function was assessed at 3 and 6 weeks. Data were analyzed using a one-way ANOVA and t-test in the SPSS data software. Researchers observed no significant changes in pulmonary function or EIB over the course of an 8-week swim season. A better understanding of treatments for asthma and EIB symptoms is needed to help abate long term respiratory limitations that may occur due to pool environment exposure. It is also important to further exam pool quality standards to provide a safe and healthy pool environment for these athletes.

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)0.001
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.210
Teacher spread0.201 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueNC Digital Online Collection of Knowledge and Scholarship (The University of North Carolina at Greensboro)Same topicIndoor Air Quality and Microbial ExposureFrench-language works237,207