Sensor Layer of a Multiparameter Single-Point Integrated 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
Microfabrication and circuit integration provide sensors with reduced size, improved performance, increased reliability, and lower cost. These microsensors can measure a variety of properties and behaviors, and are typically constructed on a range of substrate materials in combination with signal conditioning, information processing, and data-communication electronics. The challenge remains to integrate multiple sensors, each measuring different parameters with separate supporting electronics, into a single. high-density microsystem. We describe a multiple parameter medical sensor that is suitable for mounting on an active moving patient where mechanical flexibility, tight adhesion, lightweight, small size, and biocompatibility of an easily applied flat stick-on assembly at a single skin site are important considerations. Traditional microintegration technologies, such as system-in-package and system-on-chip, typically create lumped aggregations of components. In this paper, the flat architectural platform of a multiparameter sensor system is presented with microcircuitry distributed across multiple stacked layers that can be easily bent to fit body contours. The silicone-encapsulated fabrication of a thin foldable polyimide substrate with distributed surface-mount electronics is demonstrated. The measured performance results are discussed with a particular focus on the assessment of vibration-sensing elements after integration into this type of system has been described.
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 | 0.000 | 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