Exponential Sum Modeling of Reswick and Rogers Pressure-Duration Curve: A New Analysis and Model
Bibliographic record
Abstract
Reswick and Rogers model is not valid for predicting the effects of short- and long-time tissue exposures to contact pressures because it lacks intercepts. A different model, without those asymptotic properties, that could fit the shape of the curve well, could potentially provide useful information. We used modeling to test the hypotheses that an exponential model could fit Reswick and Rogers pressure-duration curve, and, if so, to determine the order of the best fit exponential model. Up to four exponential sum models were fit. Three exponentials provided the best fit [Weighted sum-of-squared residuals 72, Akaike Information Criterion 89, r=0.997]. Thereby identifying three homogeneously distinct anatomical pressure-load containing tissue compartments: skin, fat, and muscle. A fourth compartment, bone, could not be identified because of limited resolution of the data. Our results suggest that the fat pressure-load containing compartment may play an adaptive compensatory preventive role in response to pressure loads—“a cushion effect.” Exponential sum modeling of pressure-duration curves provides a new approach for studying the dynamics of compression in normal and disease states in humans, and it may be useful for practical application at the point-of-care to assist with prevention and treatment of pressure ulcers.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 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".