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Record W2298580107

An observational study of sun and heat protection during Canada Day outdoor celebration, 2003.

2006· article· en· W2298580107 on OpenAlexaffabout
David St, Urmila Chandran, Daniel Paquette, Donald J. Scholten, James F. Wilson, Eleni Galanis, Merle Becker, Frank Crane, Richard A. Lester, T Mersereau, Eugene H. Wong, D. J. Carr

Bibliographic record

VenuePubMed · 2006
Typearticle
Languageen
FieldMedicine
TopicTravel-related health issues
Canadian institutionsBC Centre for Disease Control
Fundersnot available
KeywordsObservational studyAttendanceMedicineSunburnSun protectionDemographicsSAFEREnvironmental healthCapital citySun exposureMass gatheringHeat illnessPublic healthDemographyGeographyMeteorologyNursing
DOInot available

Abstract

fetched live from OpenAlex

Attendance at summer outdoor mass gatherings may lead to heat- and sun-related illness. The purposes of this study were: (1) to estimate the proportion of people in attendance at the 2003 Canada Day celebration in the National Capital Region who used sun and heat protective items; (2) to identify factors associated with the utilization of these protective items; and (3) to provide research data to public outdoor event organizers when developing evidence-based plans for safer events. A naturalistic observational cross-sectional method was used to gather information at the 2003 Canada Day celebration in the National Capital Region on attendees' demographics, the sun and heat protective items they used and the protective resources available at the event sites. Of the 398 observed attendees, the proportion using any one of the protective items ranged from 3 percent (an open umbrella) to 51.5 percent (sunglasses). Females were more likely to use protective items more than males, and adults more likely than children. Planners of public outdoor events should consider the factors that influence the utilization of sun and heat protective behaviours and the environmental modifications that would allow participants to make safe choices.

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 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 score0.003
Threshold uncertainty score0.501

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 head0.060
GPT teacher head0.269
Teacher spread0.209 · 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 teacher head, 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

Citations1
Published2006
Admission routes2
Has abstractyes

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