Pilot Analysis of Presentations at Meetings of the American Contact Dermatitis Society and the European Society of Contact Dermatitis
Bibliographic record
Abstract
BACKGROUND: The largest meetings on contact dermatitis are those of the American Contact Dermatitis Society (ACDS) and the European Society of Contact Dermatitis (ESCD). OBJECTIVE: To document the topics presented at these meetings and their presenters' countries of origin. METHODS: Review of abstracts from the 2006 ESCD meeting and the 2005 and 2006 ACDS meetings. RESULTS: Twenty percent of ACDS presentations were on patch testing, versus 5% at the ESCD meeting (p < .001); 15% of ACDS presentations were on local reactions, versus 5% at the ESCD meeting (p < .01); 10% of ESCD presentations were on cosmetics/fragrance, versus 1% at the ACDS meetings (p = .014); and 31% of ESCD presentations were on metals and occupational topics, versus 18% at the ACDS meetings (p < .05). At the ACDS meetings, 55% of presenters were American, versus 2% at the ESCD meeting. Higher percentages of ESCD presenters were from Germany, Austria, and Switzerland (p < .001), the United Kingdom (p < .01), France and Belgium (p < .05), Italy (p < .05), and Scandinavia (p < .001). More papers from Canada (p < .001) and the rest of the world were presented at the ACDS meetings (p < .001). CONCLUSION: Significant differences exist between these meetings. There may be the potential for increased joint meetings of these societies.
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 | 0.019 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".