A Feasibility Examination Using Microwave Stripline Resonators for Low-Temperature Sensing
Bibliographic record
Abstract
A stripline transmission-line-based temperature sensor is designed and fabricated for examination of use in low-temperature environments. A custom-built chassis encloses the stripline, shielding the low-temperature sensor from environmental disturbances such as frost and condensation, which would otherwise disrupt temperature measurement. The base resonator geometry is a 6.05-mm ring, modified with a split and transmission lines (TLs) extended inward to operate at frequencies between 910 and 927 MHz over temperatures from$- 70~^{\circ }$C to$10~^{\circ }$C. The one-port sensor exploits the thermal coefficient of dielectric constant (TCD) of −459 ppm/°C of a commercial dielectric substrate. As temperature changes, so does the dielectric constant of the substrate, correlating to a shift in resonant frequency. A series of thermal cycling and stability experiments demonstrate repeatable and stable resonant frequency and temperature measurements. Several independent temperature step experiments between$- 70~^{\circ }$C and$10~^{\circ }$C are performed, resulting in a repeatable linear sensitivity of$\approx ~199$kHz/°C. The results confirm the feasibility of using microwave (MW) stripline resonant sensors on commercial substrates for low-temperature sensing.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".