Bibliographic record
Abstract
A 55-year-old Caucasian man presented to a plastic surgeon for the treatment of two lesions on his nose, first a chronic indented area with some telangiectasia on the proximal nasal bridge (Figure 1) and second a hyperkeratotic nodule with central crusting on the ala nasi that developed rapidly over several weeks (Figure 2). The surgeon appropriately diagnosed the ala nasi nodule as a squamous cell carcinoma, keratoacanthoma type, but requested an opinion from dermatology for the proximal nasal bridge indentation that he suspected to be a morpheaform or erosive basal cell carcinoma possibly requiring Mohs micrographic surgery. Upon further questioning, the patient revealed that he has had persistent erythema and problems with facial flushing for many years, particularly with alcohol, coffee, and moderate exercise. He infrequently develops papulopustular lesions. Closer clinical inspection revealed a mild erythema, telangiectases, and a hypertrophied nose. He noted that he wore an old heavy pair of glasses every day. He was notified of a coexisting diagnosis of rosacea, and various treatment options were discussed. He was pleased that he would not need any further surgery to his nose.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".