The <scp>REALITY</scp> of <scp>MINT</scp>: Caution before changing transfusion practice in myocardial infarction based on recent clinical trials
Bibliographic record
Abstract
AS has received consulting fees from CSL Vifor, Pharmacosmos, Accumen, I-Sep, Grifols, Lindis Corp, Octapharma, HbO2 Therapeutics LLC, and has served on the Data Safety Monitoring Board for RAPIDIRON trial. MJ declares no related conflicts of interest. KMT has received consulting fees from PBMe.Solutions, honoraria from Even Troop, and travel support for attending meeting from IFPBM. LSL has received consulting fee from CSL Behring and Vifor and has been board member in Society of Cardiovascular Anesthesiologists, National Board of Echocardiography and Society for Advancement of Patient Blood Management. NA has received honoraria for lectures and presentation as well as support for attending meetings and travel from Pharmacosmos. CRE has received honoraria from Pharmacosmos and Pfizer and travel support from Pharmacosmos and has served on the advisory boards for IV Iron in Cardiac Surgery and for Heart Failure for Pharmacosmos. IG has received consulting fees from Acumen, LLC, payment for participation in an advisory meeting from CSL Behring, and travel support from IFPBM and has served as a scientific associate for IFPBM. RS has received consulting fees from La Jolla, Terumo, and Encare, and honoraria from Atricure, Artivion, and Zimmer, and has served ERAS Cardiac Society. DTE has received consulting fees from Arthrex, Medela, Bioporto, and Atricure, has participated in the data safety monitoring board for Edwards Lifesciences and advisory boards for Renibus and Alexion, and has served as the president of ERAS Cardiac Society. PRT has served on Accumen Medical Advisory Board and has been a presenter for Hemosonics and CSL Vifor.
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 | 0.043 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.017 | 0.007 |
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".