Review: topical mupirocin or fusidic acid may be more effective than oral antibiotics for limited non-bullous impetigo
Bibliographic record
Abstract
Koning S, Verhagen AP, van Suijlekom-Smit LW, et al . Interventions for impetigo. Cochrane Database Syst Rev 2004;(2):CD003261. Q Which treatments are effective for impetigo? ### ![Graphic][1] Data sources: Cochrane Skin Group Specialised Trials Register (March 2002), Cochrane Central Register of Controlled Trials (Issue 1, 2002), National Research Register (2002), Medline (1966 to January 2003), EMBASE/Excerpta Medica (1980 to March 2000), LILACS (November 2001), and meta Register of Controlled Trials on the Current Controlled Trials website; hand searches of Yearbook of Dermatology (1938–66) and Yearbook of Drug Therapy (1949–66); reference lists of retrieved articles; and pharmaceutical companies. ### ![Graphic][2] Study selection and assessment: published and unpublished randomised controlled trials (RCTs) in any language that assessed any intervention for impetigo (non-bullous, bullous, secondary, and impetiginised dermatoses) in patients with diagnosed impetigo or impetigo contagiosa, preferably confirmed by bacterial culture; studies that assessed patients with broadly defined bacterial skin infections or pyoderma … [1]: /embed/inline-graphic-1.gif [2]: /embed/inline-graphic-2.gif
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 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".