Induction-response functions for frequency-domain electromagnetic mapping system for airborne and ground configurations
Bibliographic record
Abstract
Abstract A helicopter-towed electromagnetic (EM) sensor of the type typically flown in frequency-domain surveys may be towed over the ground on a trailer. The in-phase and quadrature components measured by a trailer-towed sensor will be dramatically different from those determined when the sensor is flown. For the airborne case, the in-phase and quadrature curves of the induction-response function are governed by the superposed-dipole behavior, in which flying height substantially exceeds the transmitting-receiving coil separation. In contrast, for a ground-based sensor, the coil separation substantially exceeds the sensor height, yielding the infinitely separated dipole case in which the sensor height is negligible compared to the coil separation. These two end cases — the superposed dipole and the infinitely separated dipole —yield EM amplitudes and phase angles that are very different from each other. For the superposed-dipole case of the airborne sensor, the in-phase component reaches a high positive value as the EM response approaches the inductive limit, whereas for the infinitely separated dipole case of the ground sensor, the in-phase component reaches a large negative value. Consequently, there must be a sensor height where the in-phase becomes zero at the inductive limit. This critical height is approximately 35% of the coil separation for the maximum coupled horizontal coplanar coils of the helicopter-towed EM system. The resolution of the ground sensor is superior to that of the airborne sensor, whereas the depth of exploration for the airborne sensor is superior to that of the ground sensor. This finding is to be expected from a consideration of the size of the footprint of the sensor.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".