An integrated organic circuit array for flexible large-area temperature sensing
Bibliographic record
Abstract
Traditionally, several technologies have been used for temperature sensing, including integrated silicon ^#x0394;VBEand #x0394;Vtcircuits, resistance temperature detectors, and thermocouples [1]. The organic thin-film transistor (OTFT) is a new technology suitable for temperature sensing because of two key advantages. First, OTFTs have the ability to be fabricated on flexible and large-area substrates [2]. This ability allows an OTFT temperature sensor to be used for applications such as electronic skin, biomedical thermal imaging, and structural temperature monitoring [2]. Second, the OTFT's semiconductor trap states make OTFTs highly responsive to temperature. This paper presents the first integrated OTFT temperature sensing circuit array. The array is compatible with flexible and large-area substrates, and its outputs are 22 times more responsive than the MOSFET implementation while dissipating 90nW of power per cell.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".