Proceedings of the Food and Drug Administration's public workshop on new red blood cell product regulatory science 2016
Bibliographic record
Abstract
The US Food and Drug Administration (FDA) held a workshop on red blood cell (RBC) product regulatory science on October 6 and 7, 2016, at the Natcher Conference Center on the National Institutes of Health (NIH) Campus in Bethesda, Maryland. The workshop was supported by the National Heart, Lung, and Blood Institute, NIH; the Department of Defense; the Office of the Assistant Secretary for Health, Department of Health and Human Services; and the Center for Biologics Evaluation and Research, FDA. The workshop reviewed the status and scientific basis of the current regulatory framework and the available scientific tools to expand it to evaluate innovative and future RBC transfusion products. A full record of the proceedings is available on the FDA website (http://www.fda.gov/BiologicsBloodVaccines/NewsEvents/WorkshopsMeetingsConferences/ucm507890.htm). The contents of the summary are the authors' opinions and do not represent agency policy.
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 | 0.031 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.014 | 0.016 |
| Insufficient payload (model declined to judge) | 0.033 | 0.013 |
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".