British Association of Dermatologists centenary year: standing on the shoulders of giants
Bibliographic record
Abstract
E‐mail: [email protected] Conflicts of interest: J.R.I. is Editor of the British Journal of Dermatology. D.J.G. is honorary treasurer and a trustee of the British Skin Foundation. In 2020, the British Association of Dermatologists (BAD) marks its one hundredth year since inception. One of its founding principles is to foster research to improve the care of those with skin disease. It does this in several ways including financial support for the British Skin Foundation, which makes grants available for dermatology research, and via its journals, the BJD and Clinical and Experimental Dermatology (CED). As part of the centenary celebrations a look back at some of the best papers in the BJD and CED is warranted. There are some real gems, including landmark publications introducing Sweet syndrome, orf, Lyell syndrome (toxic epidermal necrolysis, TEN), Ludwig's classification of androgenetic alopecia and the Dermatology Life Quality Index (DLQI). Let's start from the 1920s and work forwards to the present day. The paper by Cranston Low published in the October 1928 issue of The British Journal of Dermatology and Syphilis (subsequently renamed the BJD), highlights the ‘eczema–asthma–prurigo–complex’.1 It provides an early description of atopy, which in the 1920s was not well recognized, a situation that is difficult to contemplate now.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.276 | 0.250 |
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".