The<i>Staphylococcus aureus</i>Network Adaptive Platform Trial Protocol: New Tools for an Old Foe
Bibliographic record
Abstract
Staphylococcus aureus bloodstream (SAB) infection is a common and severe infectious disease, with a 90-day mortality of 15%-30%. Despite this, <3000 people have been randomized into clinical trials of treatments for SAB infection. The limited evidence base partly results from clinical trials for SAB infections being difficult to complete at scale using traditional clinical trial methods. Here we provide the rationale and framework for an adaptive platform trial applied to SAB infections. We detail the design features of the Staphylococcus aureus Network Adaptive Platform (SNAP) trial that will enable multiple questions to be answered as efficiently as possible. The SNAP trial commenced enrolling patients across multiple countries in 2022 with an estimated target sample size of 7000 participants. This approach may serve as an exemplar to increase efficiency of clinical trials for other infectious disease syndromes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".