Field tests of an experimental helicopter time-domain electromagnetic system for unexploded ordnance detection
Bibliographic record
Abstract
Abstract Field trials of a low-flying time-domain helicopter electromagnetic system designed for detection of unexploded ordnance have yielded positive and encouraging results. The system is able to detect ordnance as small as 60-mm rounds at 1-m sensor height. We examined several transmitter and receiver configurations. Small loop receivers gave superior signal-to-noise ratios in comparison to larger receiver loops at low heights. Base frequencies of 90 Hz and 270 Hz were less affected than other base frequencies by noise produced by proximity to the helicopter and by vibration of the support structure. For small ordnance, a two-lobed, antisymmetric transmitter loop geometry produced a modest signal-to-noise enhancement compared with a large single rectangular loop, presumably because the antisymmetric transmitter produces smaller eddy currents in the helicopter body, thereby reducing this source of noise. In most cases, differencing of vertically offset receivers did not substantially improve signal-to-noise ratios at very low sensor altitudes. Signal attenuation from transmitter to target and from target to receiver causes signals from smaller ordnance to quickly become indistinguishable from geological background variations, so that above a sensor height of about 3 m only large ordnance items (e.g., bombs and large caliber artillery rounds) were consistently detected.
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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 | 0.001 | 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) | 0.002 | 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 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".