A Novel Middleware Solution to Improve Ubiquitous Healthcare Systems Aided by Affective Information
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
The arousal of emotion might have consequences for physical health is a broadly acknowledged idea. Therapy for depression, prevention for heart pathologies, and rehabilitation treatments for drug addiction are just a few examples of application domains that may benefit from technologies capable of monitoring, detecting, representing, and disseminating information pertaining to patients' physical and psychological/emotional states. However, the design and development of healthcare applications of this kind is a rather challenging issue that requires to integrate sensor infrastructures, which are able to detect changes in patients' physiological and emotional states, and of sharing this information to interested caregivers, such as professional medical staff, relatives, and friends. This paper proposes the Pervasive Environment for AffeCtive Healthcare (PEACH) framework, a middleware level support for affective healthcare that incarnates these ideas and describes its effective functions in a drug addiction treatment application scenario.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it