International observational atopic dermatitis cohort to follow natural history and treatment course: TARGET-DERM AD study design and rationale
Bibliographic record
Abstract
INTRODUCTION: As new topical and systemic treatments become available for atopic dermatitis (AD), there is a need to understand how treatments are being used in routine clinical practice, their comparative effectiveness and their long-term safety in diverse clinical settings. METHODS AND ANALYSIS: The TARGET-DERM AD cohort is a longitudinal, observational study of patients with AD of all ages, designed to provide practical information on long-term effectiveness and safety unobtainable in traditional registration trials. Patients with physician-diagnosed AD receiving prescription treatment (topical or systemic) will be enrolled at academic and community clinical centres. Up to 3 years of retrospective medical records, 5 years of prospective medical records, and optional biological samples and patient-reported outcomes will be collected. The primary aims include characterisation of AD treatment regimens, evaluation of response to therapy, and description of adverse events. ETHICS AND DISSEMINATION: TARGET-DERM has been approved by a central IRB (Copernicus Group IRB, 5000 Centregreen Way Suite 200, Cary, North Carolina 27513) as well as local and institutional IRBs. No additional Ethics Committee reviews. Results will be reviewed by a publications committee and submitted to peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT03661866, pre-results.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".