Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Epidemiological information was obtained by a series of questions to experts in the field of epidemiology of transfusion from the United States, England, Australia and Denmark. Although it became clear that the methods for collecting the data had differed between the countries, useful information was obtained for all questions. The data highlighted some major differences between the countries: the incident rate for red cell transfusion varied from 44.7 to 54.1 units, for platelets from 2.0 to 6.0 units and for plasma from 4.8 to 13.8 units transfused per 1000 population per year. Age and sex distribution of transfused patients was similar in all countries. Most of the red cell products are transfused to older recipients, and the distribution between men and women is approximately equal. The distribution for platelets is over a wider age range, and the difference between men and women is marked, with men predominating in all countries. The distribution for plasma is also directed to the elderly, and there is a predominance of men. The relationship between the disease or surgical procedure and the use of blood products was similar between countries. The use of red cells in cardiovascular surgery predominated. Neoplasms and digestive disorders were also prevalent. Neoplasms, including those relating to haematology, were the main use for platelets, but cardiovascular surgery was also important. In all countries, plasma is largely used in cardiovascular surgery. Two countries provided data relating to the number of units per transfusion episode including information relating to massive transfusion. In Australia, red cell use of >or=50 units per episode was largely associated with multiple traumas. In Denmark, it was associated with gastrointestinal bleeding and various medical requests.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it