Rapid reviews versus full systematic reviews: An inventory of current methods and practice in health technology assessment: Corrigendum
Bibliographic record
Abstract
In the article entitled “Rapid reviews versus full systematic reviews: An inventory of current methods and practice in health technology assessment,” by Watt et al. in volume 24 number 2 (Spring 2008) of International Journal of Technology Assessment in Health Care, the affiliation of Stephen Blamey is incorrectly listed as Department of Health & Ageing. Dr. Blamey is the current Chair of the Medical Services Advisory Committee (MSAC). MSAC is an independent scientific committee comprising individuals with expertise in clinical medicine, health economics, and consumer matters. The Department of Health & Ageing administers funding and operations for MSAC. However, members of MSAC act independently of the Department. As Chair of MSAC, Dr. Blamey can be contacted through the Department. Dr. Blamey is not affiliated with the Department of Health and Ageing and his contribution to the above-mentioned article does not reflect its policy. Dr. Blamey wishes to apologize for this misunderstanding.
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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 | 0.190 | 0.678 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.018 | 0.028 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.016 | 0.010 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.009 | 0.009 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".