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Record W2129080466 · doi:10.1093/aje/kwk004

Comparison of Self-reported Lifetime Sun Exposure with Two Methods of Cutaneous Microtopography

2006· article· en· W2129080466 on OpenAlexafffundabout
Leonard Weiler, Julia A. Knight, Reinhold Vieth, Heidi Barnett, Ashley Wong

Bibliographic record

VenueAmerican Journal of Epidemiology · 2006
Typearticle
Languageen
FieldMedicine
TopicSkin Protection and Aging
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
FundersCanadian Breast Cancer Research Alliance
KeywordsConfidence intervalOdds ratioMedicineSkin cancerSun exposureSunlightOddsSkin typeUltraviolet radiationDemographyDermatologyCancerLogistic regressionInternal medicine

Abstract

fetched live from OpenAlex

There is currently no "gold standard" for measuring lifetime sun exposure. Exploration of alternatives to self-reports is important for examining illnesses related to ultraviolet light exposure. Using skin replicas obtained from 184 controls in a breast cancer case-control study (Toronto, Ontario, Canada, 2004-2005), the authors compared self-reported indicators of lifetime sun exposure with two measures of cutaneous microtopography, the Beagley-Gibson system and skin line counts. With the Beagley-Gibson system, significantly increased odds ratios were found for age (odds ratio (OR) = 1.10, 95% confidence interval (CI): 1.05, 1.16), spending 7 days outside per week during the summer (OR = 3.33, 95% CI: 1.48, 7.50), and lifetime number of sunlamp sessions. Significantly decreased odds ratios were found for having darker skin, ever giving birth, and ever using sunlamps. With the skin line count approach, significant positive associations were found for age (OR = 2.31, 95% CI: 1.23, 4.35), age squared, duration of working in outdoor jobs (OR = 0.88, 95% CI: 0.79, 0.98), and average number of outdoor activities per week at ages 20-29 years (OR = 1.05, 95% CI: 1.00, 1.10). While the Beagley-Gibson method was associated with more variables than the skin line count method, both methods require further refinement before graded skin replicas can be recommended as a substitute for self-report measures.

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)0.001
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 score0.280
Threshold uncertainty score0.432

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.033
GPT teacher head0.407
Teacher spread0.374 · 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

Citations6
Published2006
Admission routes3
Has abstractyes

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