Cramer-Rao Bound for Source Localization of Ingested Sources in the Human Intestine Using Finite-Element Method
Bibliographic record
Abstract
In this paper we propose a computational framework using bioelectromagnetic equations for a general electromagnetic source that can account for both RF and microwave sources. We then calculate corresponding EM scatter field using realistic, fully segmented geometry of the human tract and finite-element model. We derive the corresponding inverse model for WEC localization and estimate the location and orientation of the WEC. In order to evaluate the performance of the proposed algorithm we also derive Cramer-Rao bound which is a commonly used tool in statistical signal processing used to evaluate performance of the unbiased estimators. Using our previous work we also account for the gastric pacemaker activity and evaluate its effect on the source localization accuracy and Cramer-Rao bound. In order to provide potentially useful guidelines we examine several different configurations using different source intensities, frequencies and coil orientations. As a result by calculating the lowest possible variance of the localization algorithms we expect to propose an efficient mathematical representation for the source that enables most accurate localization. We then demonstrate applicability of our results by performing numerical simulations and comparing the estimation accuracy for various configurations.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".