Scanning the horizon of obsolete technologies: Possible sources for their identification
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to identify and rank the sources for the detection of potentially obsolete technologies (POTs). METHODS: A specific questionnaire related to the search strategies and sources used for the identification of POTs and also for ineffective, inefficient or harmful health technologies was sent to the Health Technology Assessment International's Information Resources Group (HTAi-IRG) group. With the obtained information and taking into account the sources used for the identification of new and emerging technologies, a second questionnaire was elaborated and sent to EuroScan and International Network of Agencies for Health Technology Assessment (INAHTA) members, who had to select and score them. For the final ranking, the number of votes and the median score were taken into account. RESULTS: Seven HTAi-IRG members answered to the first questionnaire. Seventeen agencies answered to the second one (thirteen EuroScan members and four more members from INAHTA), but only seven had worked in the identification of POTs and one of them using only experts for it. The remaining six agencies answered the part related to devices, diagnostics, and procedures; five of them did it for settings and programmes and only three for drugs. The Canadian Agency for Drugs and Technologies in Health (5 votes; median = 2), Cochrane Collaboration (5 votes; median = 3), NICE (4 votes; median = 1), Food and Drug Administration (4 votes; median = 1.5), and EuroScan (4 votes, median = 2) were the most relevant sources for devices and diagnostics. CONCLUSIONS: There is little experience on POTs identification. The identified sources provide mostly indirect information and further research should take place to determine the best use of them.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".