(Invited) Paper Based Wearable Standalone Wheezing Sensor - Not a Low Dimensional System
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
We present a sensor made from paper using a Do-It-Yourself (DIY) integration strategy that can be attached to the human chest like a stethoscope for real-time asthma symptom monitoring. The sensor is designed such that it resonates around the dominant frequency of wheezing (a common symptom of asthma). This helps the sensor produce large output signals, thus it can be directly integrated with a microprocessor without the need for signal amplification circuits. Matched filtering is used to extract and detect features from the acquired chest sounds for wheeze detection. The sensor successfully detects wheezing from the human chest, even when subjected to background noise and other sounds made to imitate the lungs. The sensor is connected to a smartphone via Bluetooth, enabling signal processing and further integration into digital medical electronic systems based on the Internet of Things (IoT). Bending, cyclic pressure, heat, and sweat tests are performed on the sensor to evaluate its performance under the harsh conditions of real-life scenarios.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 it