Thermodynamic rigid cushion loading indenter: A buttock-shaped temperature and humidity measurement system for cushioning surfaces under anatomical compression conditions
Bibliographic record
Abstract
A method is described for measuring the heat and water vapor dissipation characteristics of wheelchair cushions and seating systems while under simulated loading conditions. Thermal interaction between the body and seating surfaces can result in elevated tissue temperature and moisture build-up, which may increase the risk of pressure ulcers associated with prolonged ischemia or due to macerative damage. Both the materials and geometry of commercial seating systems are thought to influence the body-support surface microclimate. A thermodynamic rigid cushion loading indenter (TRCLI) has been developed to simulate the thermal and loading conditions of the body on seating surfaces. Results are reported for 32 commercially available wheelchair cushions. The results differentiate the cushions into clusters of comparable properties that offer the potential for classification of support surfaces based on their heat and water vapor dissipation performance. This study has shown that deducing the heat and water vapor dissipation characteristics of a seating system from material physical properties is of limited value because of the influences of particular design features of combinations of materials. Testing of individual products with the use of the TRCLI can, however, reliably differentiate wheelchair cushions by their ability to dissipate heat and water vapor.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".