European Guideline on Chronic Pruritus
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Elke WEISShAAr1, Jacek C. SzEpIEToWSkI2, Ulf DArSoW3, Laurent MISEry4, Joanna WALLENgrEN5, Thomas METTANg6, Uwe gIELEr7, Torello LoTTI8, Julien LAMbErT9, peter MAISEL10, Markus STrEIT11, Malcolm W. grEAVES12, Andrew CArMIChAEL13, Erwin TSChAChLEr14, Johannes rINg3 and Sonja STaNDEr15 1Department of Clinical Social Medicine, Environmental and Occupational Dermatology, Ruprecht-Karls-University Heidelberg, Germany, 2Department of Dermatology, Venereology and Allergology, Wroclaw Medical University, Poland, 3Department of Dermatology and Allergy Biederstein, Technical University Munchen and ZAUM Center for Allergy and Environment, Munich, Germany, 4Department of Dermatology, University Hospital Brest, France, 5Department of Dermatology, Lund University, Sweden, 6German Clinic for Diagnostics, Nephrology, Wiesbaden, 7Department of Psychosomatic Dermatology, Clinic for Psychosomatic Medicine, University of Giessen, Giessen, Germany, 8Department of Dermatology, University of Florence, Italy, 9Department of Dermatology, University of Antwerpen, Belgium, 10Department of General Medicine, University Hospital Muenster, Germany, 11Department of Dermatology, Kantonsspital Aarau, Switzerland, 12Department of Dermatology, St. Thomas Hospital Lambeth, London, 13Department of Dermatology, James Cook University Hospital Middlesbrough, UK, 14Department of Dermatology, Medical University Vienna, Austria and 15Department of Dermatology, Competence Center for Pruritus, University Hospital Muenster, Germany
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it