Wireless Passive Sensor for Remote pH Monitoring
Bibliographic record
Abstract
In this paper we describe a wireless passive pH sensor for high-resolution remote pH monitoring. The sensor is based on a passive LC coil resonator whose resonant frequency is monitored remotely by measuring the change in impedance of an interrogator coil coupled to the sensor coil. The sensor resonator consists of an inductive coil connected in parallel with a voltage dependent capacitor and a pH combination electrode. Change in the electrode potential in response to variations of the pH of the solution changes the capacitance, and therefore the resonant frequency of the sensor. A linear response with a 0.1 pH resolution is achieved over a 4–10 pH dynamic range. The response time of the sensor is demonstrated to be less than 30 s and is limited by the response time of the pH combination electrode. The described sensor technology is suitable for long-term remote pH monitoring in numerous fields such as biomedical sensing, environmental monitoring, industrial and chemical processing, and structural health monitoring.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".