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Record W2608752198 · doi:10.1016/j.pmedr.2017.04.012

Choctaw Nation Youth Sun Exposure Survey

2017· article· en· W2608752198 on OpenAlexaboutno aff
Dorothy A. Rhoades, Martina Hawkins, Barbara Norton, Dannielle E. Branam, Tamela Cannady, Justin Dvorak, Kai Ding, Ardis L. Olson, Mark P. Doescher

Bibliographic record

VenuePreventive Medicine Reports · 2017
Typearticle
Languageen
FieldMedicine
TopicSkin Protection and Aging
Canadian institutionsnot available
Fundersnot available
KeywordsSunburnQuarter (Canadian coin)DemographyMedicineEnvironmental healthIncidence (geometry)Sun protectionRace (biology)PsychologyGerontologyGeographyDermatology

Abstract

fetched live from OpenAlex

The incidence of skin cancer is rising among American Indians (AI) but the prevalence of harmful ultraviolet light (UVL) exposures among AI youth is unknown. In 2013, UVL exposures, protective behaviors, and attitudes toward tanning were assessed among 129 AI and Non-Hispanic (NHW) students in grades 8-12 in Southeastern Oklahoma. Sunburn was reported by more than half the AI students and most of the NHW students. One-third of AI students reported never using sunscreen, compared to less than one-fifth of NHW students, but racial differences were mitigated by propensity to burn. Less than 10% of students never covered their shoulders when outside. Girls, regardless of race, wore hats much less often than boys. Regardless of race or sex, more than one-fourth of students never stayed in the shade, and more than one-tenth never wore sunglasses. The prevalence of outdoor tanning did not differ by race, but more than three-fourths of girls engaged in this activity compared to less than half the boys. Indoor tanning was reported by 45% of the girls, compared to 20% of girls nationwide, with no difference by race. Nearly 10% of boys tanned indoors. Among girls, 18% reported more than ten indoor tanning sessions. Over one-quarter of participants agreed that tanning makes people look more attractive, with no significant difference by race or sex. Investigations of UVL exposures should include AI youth, who have not been represented in previous studies but whose harmful UVL exposures, including indoor tanning, may place them at risk of skin cancer.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.039
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
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 head0.085
GPT teacher head0.347
Teacher spread0.262 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

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