External respiratory motion: Shape analysis and custom realistic respiratory trace generation
Bibliographic record
Abstract
PURPOSE: The authors developed a realistic respiratory trace generating (RTG) tool for use with phantom and simulation studies. METHODS: The authors analyzed the extent of abdominal wall motion from a real-time position management system database comprised of 125 lung, liver, and abdominal patients to determine the shape and extent of motion. Using Akaike's information criterion (AIC), the authors compared different model types to find the optimal realistic model of respiratory motion. RESULTS: The authors compared a family of sigmoid curves and determined a four parameter sigmoid fit was optimal for over 98% patient inhale and exhale traces. This fit was also better than sin (2)(x) for 98% of patient exhale and 70% of patient inhale traces and better than sin (x) for 100% of both patient inhale and exhale traces. This analysis also shows that sin (2)(x) is better than sin (x) for over 95% of patient inhale and exhale traces. With results from shape and extent of motion analysis, we developed a realistic respiratory trace generating (RTG) software tool. The software can be run in two modes: population and user defined. In population mode, the RTG draws entirely from the population data including inter- and intra fraction amplitude and period variability and baseline drift. In user-defined mode, the user customizes the respiratory parameters by inputting the peak-to-peak amplitude, period, end exhale position, as well as controls variability in these parameters and baseline drift. CONCLUSIONS: This work provides a method of generating custom respiratory data that can be used for initial implementation and testing of new technologies.
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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 | 0.000 |
| 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 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".