Design issues with clinical experimental platelet transfusion studies
Bibliographic record
Abstract
SUMMARY Evidence‐based platelet transfusion therapy has been facilitated by a recent number of clinical trials addressing issues of optimal trigger, dose, product efficacy and adverse events. Valid results depend upon carefully planning the study including: developing a well‐defined research question and hypothesis; selecting the most appropriate study design; identifying all aspects of the optimal intervention to be studied; selecting a clinically relevant outcome measure; determining the sample size requirements; and planning the analysis a priori. Safety issues also need to be considered during the planning stage and often includes the implementation of a data safety monitoring board. Websites that provide useful information and checklists to facilitate researchers when designing clinical studies include: CONSORT ( http://www.consort‐statement.org/index.html ) and the ICH (International Conference on Harmonization) of Technical Requirements for Registration of Pharmaceutical for Human use ( http://www.ich.org ).
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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 | 0.375 | 0.423 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.008 | 0.010 |
| 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; 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".