Abstracts of the 9th Annual Symposium on Hidradenitis Suppurativa Advances 2024
Bibliographic record
Abstract
journal were collected through a call for submissions and were selected for publication following review by external experts of the Hidradenitis Suppurativa Foundation (HSF) and the Canadian Hidradenitis Suppurativa Foundation (CHSF) abstract review committee.The Hidradenitis Suppurativa Foundation (HSF) and the Canadian Hidradenitis Suppurativa Foundation (CHSF) as a whole or its Advisory Board and Executive Committee (EC) or appointed Scientific Committees, or its members, or the publisher, do not take any responsibility for the completeness or correctness of data, or references given by authors in publications and presentations at the 9th Annual Symposium on Hidradenitis Suppurativa Advances.It is not within the remit of The Hidradenitis Suppurativa Foundation (HSF) and the Canadian Hidradenitis Suppurativa Foundation (CHSF) or their advisory committees, or the publisher, to seek clarification or detailed information from authors about data in submitted abstracts.Moreover, it is not within the scope of The Hidradenitis Suppurativa Foundation (HSF) and the Canadian Hidradenitis Suppurativa Foundation (CHSF) and their committees, or the publisher, to monitor potential conflicts of interest of the abstract authors or to monitor compliance with any legal obligations, for example, reporting requirements or regulatory actions.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.073 | 0.030 |
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".