The approach taken to reducing the risk of transfusion related acute lung injury in Canada
Bibliographic record
Abstract
Transfusion related acute lung injury (TRALI) has become a major reported cause of severe transfusion reactions and mortality. Over the past four years significant changes have been taken in Canada in order both to improve the recognition of the risk and to decrease its incidence. An international meeting was held in April of 2004 entitled "Towards an Understanding of TRALI". As a result of the analysis and recommendations from this meeting, the Canadian Blood Services established an ongoing review committee and established a laboratory diagnostic facility to identify at risk donors and recipients. A system has been developed to identify implicated donors and exclude them from the blood donor pool. Other steps have been taken to exclude potentially high risk donors, such as previously pregnant females, from the plasma and platelet donor pool. A considerable amount of education also has been offered to clinical services in the country. This paper summarizes the definitions, categorizations of implicated donors, and the ongoing precautionary activities related to plasma products. Noted within the article are the methods used for locating and selecting data. These were primarily based on the international TRALI conference in 2004, and from ongoing discussions and information provided by the Canadian Blood Services TRALI Review Committee. No ethics referral or approval was requested, and a summary is included in 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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".