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Record W2163108662 · doi:10.1080/09603120400018899

Exposure to carbon monoxide during indoor karting

2004· article· en· W2163108662 on OpenAlexaff
Benoît Lévesque, David Bellemare, Guy Sanfaçon, Jean-François Duchesne, Denis Gauvin, Henri Prud'homme, Pierre Ayotte

Bibliographic record

VenueInternational Journal of Environmental Health Research · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsInstitut National de Santé Publique du QuébecCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsCarbon monoxideIndoor air qualityEnvironmental scienceEnvironmental chemistryChemistryEnvironmental engineering

Abstract

fetched live from OpenAlex

Karting is a recreational activity of increasing popularity and it is often practiced indoors leading to build up of toxic gases in ambient air. This study was realised to verify the level of exposure to carbon monoxide (CO) in ten male racers (Age: 15 to 49 years old) during a 45-min race. The alveolar concentration of CO (alvCO) for each participant was measured before and after the race. The ambient CO level was determined continuously from the start to the end of the race with two detectors. Mean ambient air CO concentration was 41 ppm and the average increase of alvCO for the ten subjects was 16.2 ppm corresponding to about 3% COHb. Based on these results and on the Coburn model, a reference limit of 25 ppm was suggested for a 1 h exposure during indoor karting. At the request of the public health authorities, some modifications were made to the karts, to the CO monitoring surveillance system and to the ventilation system of the building. CO concentrations were monitored thereafter. The guideline of 25 ppm for 60 min was always respected.

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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.108
GPT teacher head0.432
Teacher spread0.323 · 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

Citations7
Published2004
Admission routes1
Has abstractyes

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