Additional file 1 of Explaining the variation in the attained power of a stepped-wedge trial with unequal cluster sizes
Bibliographic record
Abstract
Additional file 1: S.1 List of all evaluated scenarios. S.2 Cluster size re-distribution Calculation. S.3.1 Risk of obtaining low vs ICC for scenarios with equal distribution of clusters. S.3.2 Risk of obtaining low vs CV for scenarios with equal distribution of clusters. S.4.1 The relationship between TTC and attained power for all scenarios. S.4.2 The relationship between TGI and attained power for all scenarios. S.5 Distribution of the coefficient for TGI before and after adjusting for TTC. S.6 The RMSPE, maximum absolute prediction error, and average absolute prediction error for all scenarios. S.7 Side-by-side violin plot showing the distribution of difference between the predicted and simulated attained powers for the allocations not used in model fitting for scenario #64 and #103.
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 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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.343 | 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 teacher head, 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".