Dual-Band Split Ring Resonator Sensor for Independent Simultaneous Multi-Material Identification
Bibliographic record
Abstract
This paper presents a novel microwave reader-tag-based sensor designed for the real-time, simultaneous measurement of the properties of two different materials under test. Conventional techniques for evaluating multiple materials typically depend on individual sensors for each material, which increases complexity and limited data integration. Our proposed sensor addresses these challenges by integrating both sensing capabilities into a single device. Utilizing a transmission line (TL) as the reader and two split ring resonator (SRR)-based tags, this sensor achieves two distinct resonances at specified frequencies, which are completely isolated from each other. Each resonance is responsible for sensing changes in the electrical properties of its surrounding environment. We highlight the advantages of employing this sensor for real-time monitoring and analysis, emphasizing its promising potential in various applications such as precision agriculture, biomedical engineering, and more. The integration of independent dual-material sensing in a single planar microwave sensor not only simplifies the measurement process but also enhances data accuracy and reliability.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".