Bibliographic record
Abstract
The Common Technical Document(CTD) is part of the ICH(International Conference on Harmonization) program for developing global, harmonized guidelines for the contents and format of new drug and biologic products applications to be submitted to regulatory agencies in the ICH regions. The CTD is divided into 5 modules : 1. Region specific administrative and prescribing information 2. High level summary 3. Quality -chemical, pharmaceutical and biological documentation 4. Non-clinical study reports 5. Clinical study reports. The potential advantages of CTD can be extensive. A pharmaceutical companies could save in resources and time, so that they could facilitate simultaneous submissions in ICH regions. Also, CTD could provide a more efficient evaluation process with regulators, as well. Finally, a faster availability of new medicines is expected in the future. The CTD was first agreed upon in 2000 and now required inthe EU, Japan, Canada and Switzerland and is strongly encouraged in the US. In Korea, CTD submissions will be accepted by KFDA for New Drug Application in March, 2009. In this session, a general overview of the CTD documents and a detailed introduction with each modules will be presented. The background, scientific and regulatory aspects of CTD documents will be focused.
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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 | 0.088 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.018 | 0.016 |
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".