A Procedure for Quantifying a UAV-borne Magnetometer Vertical Setback Distance
Bibliographic record
Abstract
Summary Within this study, a vertical buzz test methodology is applied to characterize the distance at which the electromagnetic interference generated by a UAV platform attenuates below the sensitivity threshold of a high-resolution magnetometer in a controlled setting. A DJI Wind 4 heavy-lift, multi-rotor UAV platform was used to characterize the spatial extent of the electromagnetic interference generated inflight. The vertical setback distance of a UAV-borne aeromagnetic system was characterized using a vertical buzz test maneuver in a magnetically quiet area. Through conducting the characterization test, it was determined that the DJI Wind 4 with a 2.2 kg payload required a vertical setback distance of approximately 5 m when surveying with a magnetometer employing a sensitivity of 0.01 nT. Furthermore, it was determined that a magnetometers vertical setback distance is unique for each specific combination of UAV platform and magnetometer employed within a UAV-borne aeromagnetic system. Based on previous tests, using the same magnetometer and methodology, the vertical setback distance was determined to be 3 m, for both a DJI - S900 and M600. Therefore, the assessment shown herein should be conducted to characterize the vertical setback distance for specific UAV magnetometry systems (each platform and magnetometer) prior to conducting surveys.
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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 | 0.000 | 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 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".