Nevus count associations with pigmentary phenotype, histopathological melanoma characteristics and survival from melanoma
Bibliographic record
Abstract
Although nevus count is an established risk factor for melanoma, relationships between nevus number and patient and tumor characteristics have not been well studied and the influence of nevus count on melanoma-specific survival is equivocal. Using data from the Genes, Environment and Melanoma (GEM) study, a large population-based study of primary cutaneous melanoma, we evaluated associations between number of nevi and patient features, including sun-sensitivity summarized in a phenotypic index, and tumor characteristics. We also assessed the association of nevus count with melanoma-specific survival. Higher nevus counts were independently and positively associated with male gender and younger age at diagnosis, and they were inversely associated with lentigo maligna histology. We observed a borderline significant trend of poorer melanoma-specific survival with increasing quartile of nevus count, but little or no association between number of nevi and pigmentary phenotypic characteristics or prognostic tumor features.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".