The Subjective Comfort Test of Autism Hug Machine Portable Seat
Bibliographic record
Abstract
This preliminary study proposes to investigate (i) the mean comfortable deep pressure of Autism Hug Machine Portable Seat (AHMPS) manual pull and inflatable wrap models; and (ii) the effect of using AHMPS in reducing anxiety in children with autism spectrum disorder (ASD). The first phase was done to determine the comfort test. Fifteen healthy adolescents (13 men and 2 women; aged 19-25 years) individuals volunteered to participate in the comfort test in determining the pressure of AHMPS, both manual pull, and inflatable wrap. The second phase was completed in children with ASD, in which the comforting pressure from the first phase was then applied to five children with ASD (4 boys and 1 girl; aged 8-15 years) from the Putra Mandiri Public Special School Semarang. All children were administered both the AHMPS inflatable wrap and manual pull as a deep pressure apparatus while traveling by bus. A pulse oximeter was used to measure heart rate variability (physiological arousal). The mean comfort pressure was obtained from 15 healthy subjects, which was 0.81 psi on the chest and 0.80 psi on the thigh for the manual pull; and 0.65 psi on the chest and 0.45 psi on the thigh for the inflatable wrap. In the second phase, the AHMPS manual pull did not significantly decrease heart rate with p=0.114, but the AHMPS inflatable wrap significantly decreased heart rate with a significance value of p=0.037. We conclude, therefore, the AHMPS inflatable wrap decreases physiological arousal in children with ASD.
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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 | 0.000 | 0.002 |
| 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) | 0.002 | 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".