On the Development and Edification of Canadian Guidelines for the Pharmacoeconomic Evaluation
Bibliographic record
Abstract
AIM:To put forward the suggestions for standardizing the pharmacoeconomic research.METHODS:The background of formulation and main points of Canadian Guidelines for the Pharmacoeconomic Evaluation were introduced and its recent development was described.At the same time,we put forward our tentative plan about establishing Chinese guidelines for the pharmacoeconomic evaluation.RESULTS CONCLUSION:A series of guidelines for the pharmacoeconomic evaluation should be established,which is approved by departments of social safeguard,drug supervision and public health administration,to standardize the pharmacoeconomic research.The goverment should make corresponding policy publicized and make pharmacoeconomic evaluation connect with drug price,clinically rational drug use,catalog of classified management of drugs and catalog of drugs in medical insurance.A pharmacoeconomic framework,which conforms China's national conditions and is controlled by goverment,will established.
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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 | 0.018 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".