Ultrasonic Detection of the Intravascular Free Gas Phase in Research on Diving
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
Abstract The article presents a unique atypical application of the sonography technique and a methodological description of the introduction of this technique to research. The Bayesian approach applied to validation of the Doppler method for intravascular detection of the free gas phase instead of typical statistical inference has been demonstrated in the article. It describes the place of this method in the diving research work conducted in the Polish Naval Academy without any detailed analysis of the results achieved in the studies on decompression supported by ultrasonic detection of the free gas phase in venous vessels. It is a commonly held opinion that Doppler ultrasonic detection of the intravascular free gas phase is not a procedure that can be particularly useful in decompression research. The main objection is that detection of the free gas phase in venous vessels is a weak function to predict the presence of the free gas phase in tissues and arterial blood, so this method is not suitable for assessing the risk of decompression. Only a few countries disagree with this commonly held view and use this method to assess the risk of decompression in decompression studies. France has introduced detection of the free gas phase in venous vessels for diving research and then, together with Canada, improved this method, and developed it to a standard form. Based on the published results of the Canadian research, the technique was evaluated at the Naval Academy using statistical methods. The Academy accepted and adopted the results of this research and started to use this method in its own research on decompression over 25 years ago and continues to use it to great effect.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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