Real‐time compensation of magnetic data acquired by a single‐rotor unmanned aircraft system
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT Two methods for low‐altitude calibration of a single‐rotor unmanned aircraft system using a real‐time compensator are tested: (1) a stationary calibration where the unmanned aircraft system executes manoeuvres while hovering in order to minimize ambient field changes due to the local geology; and (2) an adapted box calibration flown in four orthogonal directions. Both methods use two compensator‐specific limits derived from established methods for manned airborne calibration: the lowest frequency used by the compensator for the calibration algorithm and the maximum variation of the ambient magnetic intensity experienced by the unmanned aircraft system during calibration. Prior to flying, the unmanned aircraft system was magnetically characterized using the heading error and fourth difference. Magnetic interference was mitigated by extending the magnetometer‐unmanned aircraft system separation distance to 1.7 m, shielding, and demagnetization. The stationary calibration yielded an improvement ratio of 8.595 and a standard deviation of the compensated total magnetic intensity of 0.075 nT (estimated Figure‐of‐Merit of 3.8 nT). The box calibration also yielded an improvement ratio of 3.989 and a standard deviation of the compensated total magnetic intensity of 0.083 nT (estimated Figure‐of‐Merit of 4.2 nT). The stationary and box calibration solutions were robust with low cross‐correlation indexes (1.090 and 1.048, respectively) when applied to a non‐native data set.
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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 | 0.000 | 0.000 |
| 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 it