Analysis of Inductively Coupled RFID Marker Localization Methods
Why this work is in the frame
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Bibliographic record
Abstract
The presented paper is focused on analysis of two methods of marker localization. The markers are passive RFID transponders (without or with identification chip) consisting of tuned LC circuit and being used to mark and trace underground networks such as cables and pipes. Localization of the marker is based on evaluation of signal amplitude received from the excited marker, i. e. it is RSSI based localization method. The excitation of marker can be periodically repeated or continuous. In the first case the localization process consists of two stagesexcitation and receiving of marker damped oscillations, in the second case the amplitude of continuously generated excitation signal is decreased by vicinity of the marker. Both localization methods are mathematically analyzed by modeling of their circuits using differential equations. The results of analysis are used to compare both methods and to evaluate their suitability for practical utilization.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| 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 it