A Formally-Verified Safety System for Closed-Loop Anesthesia
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
The benefits of closed-loop control of anesthesia in terms of drug usage, robustness to inter-patient variability and postoperative outcomes have been demonstrated in a number of clinical studies. However, to obtain regulatory approval for such systems to be employed as medical devices in operating rooms, patient safety must be demonstrated. This paper formalizes a previously published safety system for closed-loop anesthesia using formal model verification techniques. This safety system specifies safety constraints on the patient states based on the therapeutic window of propofol. To verify feasibility of the safety constraints in all situations, a finite number of simulation scenarios can be performed. However, the formal methods verify the feasibility problem for all possible admissible inputs and states without the need for simulation. The formalized safety system for closed-loop anesthesia guarantees that the patient states stay within safety constraints.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| 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 it