Issue Information
Bibliographic record
Abstract
Rapid Communication must present new fi ndings of suffi cient importance to justify their accelerated acceptance.They should follow the general arrangement of research papers with the exception that no abstract or introduction are required.The fi rst paragraph should include the reason for the study and the main fi ndings.They should not exceed 8 double-spaced manuscript pages in length, including fi gures, tables and references.Proofs are checked by the Editor and not sent to the author.Review will be rapid, and once accepted, the paper will be included in the next available issue. Short reports, Case reportsThey may include up to 1100 words of text, two fi gures or tables and up to 12 references.A summary of up to 100 words should be followed by continuous text, subdivided if appropriate.Short reports: Short reports describing completed work on signifi cant novel developments into scientifi c or clinical aspects of transfusion medicine may be published.Short reports could include important preliminary observations, short methods papers, therapeutic advances, and any signifi cant scientifi c or clinical observations which are best published in this format.Publication of initial results which will lead to more substantial papers will generally be discouraged. Case reports:The submission of Case Reports is not encouraged, but they will be considered if the report includes novel scientifi c material or is of extraordinary clinical interest.Case reports should include a brief description of the case and a comment section discussing the salient features in the context of the World literature.Letters to the Editor Letters to the Editor are welcome but should contain no more than 450 words and a maximum of fi ve references.Presentation of Manuscripts Papers should be structured as follows: (a) Title Page, (b) Structured abstract, (c) Text, (d) References, (e) Figure and Table Legends, (f) Figures and Tables.
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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.918 | 0.908 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".