A CMOS Oscillators-Based Smart Temperature Sensor for Low-Power Low-Cost Systems
Bibliographic record
Abstract
This paper proposes a CMOS oscillators-based smart temperature sensor with a SAR (Successive Approximation Register) search algorithm. To reduce the cost and release the number of bits, a temperature-dependent delay circuit (TDDC) composed of a thermal ring oscillator and a fixed-gain time amplifier was used to generate a thermal sensing delay proportional to the test temperature. An adjustable reference delay circuit (ARDC) composed of another thermal compensation ring oscillator and an adjustable-gain time amplifier was used to program a reference set-point delay. For digital output coding, a SAR control logic was adopted for selecting the optimal reference delay of the ARDC to approximate the thermal delay of the TDDC through the help of a time comparator. The chip size of the proposed oscillators-based sensor with 11 output bits was 0.25 mm2, which is less than the 0.6 mm2 of its delay-line-based predecessor with a 10 output bits in the same 0.35-μm TSMC CMOS process [1]. The measurement errors were within ±0.6 °C in the temperature range of 0 °C to 90 °C after two-point calibration for eight packaged chips.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".