Long-term Likelihood of Patch Testing, Academic Practice, and American Contact Dermatitis Society Membership Among North American Alexander Fisher Award Winners From 1989 to 2012
Bibliographic record
Abstract
BACKGROUND: The Alexander Fisher Award (AFA) recognizes excellence in research among dermatology residents or medical students who make formal presentations at the annual American Contact Dermatitis Society (ACDS) meeting. OBJECTIVE: The aim of the study was to investigate long-term likelihood of patch testing, academic practice, and society membership among Alexander Fisher Award winners (AFAWs). METHODS: The AFAWs from 1989 to 2012 were identified with Internet searches to obtain their current practice location. Each practice was contacted by phone, and staff was asked whether the AFAW performed patch testing. Current ACDS membership was confirmed by ACDS leadership. Academic status was assessed by university association on practice Web sites. RESULTS: Sixty-two awards were presented to 60 individuals from 1989 to 2012. Fifty AFAWs are actively practicing dermatology in the United States (n = 43) and Canada (n = 7). Of 50 practicing AFAWs, 18 (36%) are active patch testers, 29 (58%) do not perform patch testing, and 3 (6%) could not be reached or staff declined to answer. Of the 50, 14 (28%) practice in an academic setting, and 10 (20%) are current ACDS members.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".