Automated unsupervised respiratory event analysis
Why this work is in the frame
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Bibliographic record
Abstract
We recently presented a comprehensive automated off-line method for supervised respiratory event classification from uncalibrated respiratory inductive plethysmography signals. This method required training with a sample of clinical measurements classified by an expert. This human intervention is labor intensive and involves subjective judgments that may introduce bias to the automated classification. To address this we developed a novel method for unsupervised respiratory event classification, named AUREA (Automated Unsupervised Respiratory Event Analysis). This paper describes the algorithm underlying AUREA and demonstrates its successful application to respiratory signals acquired from infants in the postoperative recovery room. The advantages of AUREA are: first, it provides real-time classification of respiratory events; second, it requires no human intervention; and lastly, it has substantially better performance than the supervised method.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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