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Record W2127842714 · doi:10.1158/1055-9965.epi-07-0560

Smoking, Parkinson's Disease, and Melanoma

2007· letter· en· W2127842714 on OpenAlexfundaboutno aff
William B. Grant

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2007
Typeletter
Languageen
FieldMedicine
TopicSkin Protection and Aging
Canadian institutionsnot available
FundersVitamin D Society
KeywordsDiseaseMelanomaRisk factorBasal cell carcinomaObservational studyIncidence (geometry)CancerParkinson's diseaseSkin cancerOncologyMedicineBasal cellInternal medicineDermatologyPsychologyCancer research

Abstract

fetched live from OpenAlex

To the Editors: The recent article on incidence of cancer after diagnosis of Parkinson's disease is strongly confirmatory that risk of melanoma is significantly increased whereas risk of smoking-related cancers is reduced, albeit nonsignificantly (1). This finding was thought to suggest a gene-environment interaction, and one hypothesis was given related to the detoxifying enzyme P450 D6. However, no clear biological explanation was given for the melanoma finding.It should be noted that smoking has been found inversely related to risk of melanoma in four observational studies (2-5). This is in contradistinction to the case for basal cell carcinoma and squamous cell carcinoma of the skin, for which smoking is a risk factor (4). Again, no clear biological explanation has been provided. However, combining the results of ref. 1 with those of refs. 2-5, it seems that the same mechanism related to Parkinson's disease that reduces the risk of smoking-related cancers also increases the risk of melanoma. Perhaps this suggestion will be useful for both sets of studies.I receive funding from the UV Foundation (McLean, VA) and the Vitamin D Society (Canada) and expect funding from the European Sunlight Association.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.052
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.062
GPT teacher head0.366
Teacher spread0.304 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations4
Published2007
Admission routes2
Has abstractyes

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