Sensitivity-Enhanced CSRR-Loaded SIW Chipless Tag for Real-Time Coating Assessment on Medical Implants
Bibliographic record
Abstract
In this study, a new chipless Complementary Split-ring Resonators (CSRR) loaded Substrate Integrated Waveguide (SIW) tag is coupled with a coplanar antenna for real-time sensing and detection. This sensor was created for real-time monitoring of lubricant evaporation on surfaces that have been infused with lubricant. The stability of the lubricating layer is a crucial determinant for the efficient operation of these coatings. The proposed sensor consists of an ultrawide-band antenna as a reader to couple power to the CSSR-loaded SIW sensing tag. The sensor design and operation have been carefully confirmed using both simulation and measurements, confirming its capacity to detect lubricant evaporation with high sensitivity. With 0.1 MHz frequency shift in resonance frequency per 1 µL of lubricant, this sensor stands as a significant advancement in the field of medical implant technology, offering a real-time solution for ensuring the effectiveness of lubricant-infused coatings since their assessment is necessary to minimize complications associated with medical implants, such as the non-specific adhesion of blood components and bacteria.
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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 | 0.001 |
| 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 | 0.001 | 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 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".