Paper as a Platform for Sensing Applications and Other Devices: A Review
Bibliographic record
Abstract
Paper is a ubiquitous material that has various applications in day to day life. A sheet of paper is produced by pressing moist wood cellulose fibers together. Paper offers unique properties: paper allows passive liquid transport, it is compatible with many chemical and biochemical moieties, it exhibits piezoelectricity, and it is biodegradable. Hence, paper is an attractive low-cost functional material for sensing devices. In recent years, researchers in the field of science and engineering have witnessed an exponential growth in the number of research contributions that focus on the development of cost-effective and scalable fabrication methods and new applications of paper-based devices. In this review article, we highlight recent advances in the development of paper-based sensing devices in the areas of electronics, energy storage, strain sensing, microfluidic devices, and biosensing, including piezoelectric paper. Additionally, this review includes current limitations of paper-based sensing devices and points out issues that have limited the commercialization of some of the paper-based sensing devices.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".