The <scp>N</scp>ational <scp>H</scp>eart, <scp>L</scp>ung, and <scp>B</scp>lood <scp>I</scp>nstitute <scp>R</scp>ecipient <scp>E</scp>pidemiology and <scp>D</scp>onor <scp>E</scp>valuation <scp>S</scp>tudy (<scp>REDS</scp>‐<scp>III</scp>): a research program striving to improve blood donor and transfusion recipient outcomes
Bibliographic record
Abstract
BACKGROUND: The Recipient Epidemiology and Donor Evaluation Study-III (REDS-III) is a 7-year multicenter transfusion safety research initiative launched in 2011 by the National Heart, Lung, and Blood Institute. STUDY DESIGN AND METHODS: The domestic component involves four blood centers, 12 hospitals, a data coordinating center, and a central laboratory. The international component consists of distinct programs in Brazil, China, and South Africa, which involve US and in-country investigators. RESULTS: REDS-III is using two major methods to address key research priorities in blood banking and transfusion medicine. First, there will be numerous analyses of large "core" databases; the international programs have each constructed a donor and donation database while the domestic program has established a detailed research database that links data from blood donors and their donations, the components made from these donations, and data extracts from the electronic medical records of the recipients of these components. Second, there are more than 25 focused research protocols involving transfusion recipients, blood donors, or both that either are in progress or are scheduled to begin within the next 3 years. Areas of study include transfusion epidemiology and blood utilization, transfusion outcomes, noninfectious transfusion risks, human immunodeficiency virus-related safety issues (particularly in the international programs), emerging infectious agents, blood component quality, donor health and safety, and other donor issues. CONCLUSIONS: It is intended that REDS-III serve as an impetus for more widespread recipient and linked donor-recipient research in the United States as well as to help assure a safe and available blood supply in the United States and in international locations.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.078 | 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".