Evidence-based diagnosis of tuberculosis: Resources for the medical microbiologist
Bibliographic record
Abstract
Evidence-based clinical practice (EBCP) is a well-accepted approach in clinical medicine. The goal of EBCP is to successfully apply objective research evidence to enhance clinical practice and improve patient outcomes. EBCP requires us to base our clinical decisions on the best available evidence regarding a diagnostic, an intervention or a preventive measure. Evidence-based diagnosis is an integral part of EBCP and the rational use and application of diagnostic tests must be directed by high-quality evidence to determine the real impact of diagnostic tests on clinical practice and patient management. Evidence-based diagnosis is slowly gaining prominence. The Cochrane Collaboration, for example, recently began publishing systematic reviews on diagnostic test accuracy in the Cochrane Library.
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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 | 0.016 | 0.097 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.012 | 0.027 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".