Bibliographic record
Abstract
This is a pilot study comparing phonocardiographic (PCG, or heart sound) monitoring locations used during anaesthesia and surgery. Heart sounds from anaesthetised surgical patients were simultaneously recorded from a precordial stethoscope, an esophageal stethoscope, and a special endotracheal tube (ETT) designed for PCG monitoring (Teves ETT). These heart sounds were then analysed using digital signal processing techniques. The first heart sounds (S1) were characterized using signal-to-noise ratio estimates, maximum-to-minimum amplitude differences, and S1 power spectra. The first heart sound obtained from the esophageal stethoscope had the best signal strength and clarity. However, the strength and clarity of the first heart sound obtained from the precordial stethoscope and Teves ETT were quite satisfactory. Thus, from a signal analysis perspective there is little difference between S1 obtained from the different monitoring sites. Consequently a choice of PCG monitoring site should be based on practical considerations such as patient safety or ease of use.
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".