Bibliographic record
Abstract
17000 Background: In the last decade, the Program in Evidence-based Care (PEBC), the guideline initiative of the cancer system in Ontario, Canada, has evolved dramatically. In addition to providing recommendations to facilitate decisions of clinicians (clinical practice guidelines), PEBC reports provide recommendations to facilitate decisions regarding universal drug funding, resource allocation, models of care, and the organization of the cancer system. For many of these issues, there is little in terms of traditional evidence, regardless of study design. As such, extending and building upon traditional notions of evidence and methodologies to gather new kinds of evidence have been required. Methods and Results: The PEBC has evolved the way it which conceives of evidence, the methods used to assemble and appraise evidence, and the role of evidence in decision making. To this end, environmental scan and consensus methods, in addition to standard systematic review methodology, are employed. The environmental scan methodology we use includes systematic and transparent internet searches of, and/or direct inquires to, organizations in jurisdictions determined, a priori, to be generalizable to the Ontario experience. Here, evidence comes in the form of organizational reports, case studies and evaluation data. These methods continue to be refined and tested. The consensus methodology we use is a modified Delphi technique. To date, these methods have been applied to various topics including standards for diagnostic assessment programs, surgical oncology and systemic therapy models of care, patient education, multidisciplinary case conferences, patient safety, and treatment of rare diseases. Evaluations of these reports have been generally positive (approval rating range: 56% to 75%) but noticeably more varied than approval ratings of our clinical practice guidelines that have relied primarily on traditional systematic review methodology (approval ratings rarely below 80%). Conclusions: The PEBC's notions of evidence continue to evolve as does the refinement and testing of new methodologies. Through this evolution, we are now able to provide advice on issues we would otherwise be unable to using traditional methods only, while still remaining true to our core principles of being participatory, rigorous, systematic and transparent. No significant financial relationships to disclose.
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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 | 0.311 | 0.620 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.032 | 0.020 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.033 | 0.036 |
| Open science | 0.010 | 0.022 |
| Research integrity | 0.013 | 0.019 |
| Insufficient payload (model declined to judge) | 0.024 | 0.007 |
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".