Changes to the CDR Submission Guidelines for Manufacturers and Canadian Expert Drug Advisory Committee Terms of Reference 1. Common Drug Review Submission Guidelines for Manufacturers The Criteria for Resubmissions (Section 1.3.1) on page 16 of the Common
Bibliographic record
Abstract
Guidelines for Manufacturers have been revised. Please note that the second criterion for filing resubmissions now states: New Information becomes available after notice of final CEDAC recommendation not to list has been issued. The new version of the Common Drug Review Submission Guidelines for Manufacturers is dated December 1, 2004 and is posted on the CDR section of the CCOHTA website.. 2. Canadian Expert Drug Advisory Committee (CEDAC) Terms of Reference Section 9.5 has been amended to include the Vice President of CDR and Canadian Optimal Medication and Prescribing Utilization Service as a meeting attendee at CEDAC meetings. Section 9.8 has been amended to provide clarity that CEDAC has the authority to make a recommendation for all submissions to CDR. The revised CEDAC Terms of Reference are dated December 1, 2004 and are posted on the CDR section of the CCOHTA website (www.ccohta.ca).
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 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 | 0.035 | 0.201 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.008 | 0.003 |
| Research integrity | 0.013 | 0.008 |
| Insufficient payload (model declined to judge) | 0.252 | 0.298 |
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 source (direct Gemma or distilled Codex), 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".