Addressing platelet insecurity – A national call to action
Bibliographic record
Abstract
Eric Gehrie: Honorarium from Cerus Corporation; Consultancies from Grifols Diagnostics and Instrumentation Laboratories. Editorial Board, Transfusion. Pampee P. Young: Consultancy from Fresenius Kabi; Equity ownership in Eluciderm. Sridhar V. Basavaraju: None. Arthur Bracey: Associate Editor, Transfusion; American Red Cross Medical Advisory Committee; Common Spirit Health—Blood Therapeutic Clinical Council. Andrew Cap: Consultancy from Velico Medical; Equity ownership in Velico Medical; Associate Editor, Transfusion. Liz Culler: None. Nancy Dunbar: None. Mary Homer: None. Iris Isufi: Honoraria from Gilead Sciences; consultancies to Bristol-Myers Squibb Company, Janssen Biotech, Inc, ADC Therapeutics, Abbvie, Inc, Caribou Biosciences, Genmab Inc, and Incyte Corporation. Rob Macedo: None. Tanya Petraszko: Abstract Review Committee, AABB. Glenn Ramsey: Honorarium from Immucor, Inc. Christopher A. Tormey: None. Richard Kaufman: Consultancy to Belmont Medical Technologies; Data monitoring committee, Cellphire Therapeutics; Editor-in-Chief, Transfusion. Edward Snyder: Contracted research sponsored by Cerus, Corp; Associate Editor, Transfusion; Medical Advisory Council, American Red Cross. Data S1. Supporting Information. Data S2. Supporting Information. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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 | 0.032 | 0.051 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.007 | 0.014 |
| Research integrity | 0.039 | 0.040 |
| Insufficient payload (model declined to judge) | 0.084 | 0.026 |
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".