Accelerating Global Deletion of the Abnormal Toxicity Test for vaccines and biologicals. Planning common next steps. A workshop Report
Bibliographic record
Abstract
This online workshop Accelerating Global Deletion of the Abnormal Toxicity Test for vaccines and biologicals. Planning common next steps was organized on October 14th, 2021, by the Animal Free Safety Assessment Collaboration (AFSA), the Humane Society International (HSI), the European Federation of Pharmaceutical Industries and Associations (EFPIA), in collaboration with the International Alliance of Biological Standardization (IABS). The workshop saw a participation of over a hundred representatives from international organizations, pharmaceutical industries and associations, and regulatory authorities of 28 countries. Participants reported on country- and region-specific regulatory requirements and, where present, on the perspectives on the waiving and elimination of the Abnormal Toxicity Test. With AFSA, HSI, EFPIA and IABS representatives as facilitators, the participants also discussed specific country/global actions to further secure the deletion of ATT from all regulatory requirements worldwide.
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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 | 0.073 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.023 | 0.008 |
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".