Evidence‐based decision making and asthma in the internet age: the tools of the trade
Bibliographic record
Abstract
At the dawn of the Information Age, the practice of evidence-based decision making (EBDM) is still hindered by many important barriers related to the decision makers, to the evidence per se or to the health system. Some of these barriers, particularly those related to the distillation, dissemination and packaging of research evidence, could be overcome by recent and ongoing developments in portable/wearable computers, internet appliances, multimedia and wireless broadband internet traffic. This article describes specific EBDM-related tools, with emphasis on internet-enabled "how to" books; and tools to improve the quality of reporting research, to formulate questions; to search for evidence; to access journals, systematic reviews and guidelines; to interact with organizations promoting EBDM; and to tailor evidence to individual cases. However, thinking that all barriers to the practice of EBDM could be solved by fancy information technology is naïve. Barriers related to the generation, interpretation, integration and use of the evidence demand more complex and perhaps unfeasible solutions, as overcoming them will require substantial changes in the structure of the health system, in the politics of science and in the way in which humans think and behave.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".