The Canadian Forces ILDS: a militarily fielded multisensor vehicle-mounted teleoperated landmine detection system
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Improved Landmine Detection System (ILDS) is intended to meet Canadian military mine clearance requirements in rear area combat situations and peacekeeping on roads and tracks. The system consists of two teleoperated vehicles and a command vehicle. The teleoperated protection vehicle precedes, clearing antipersonnel mines and magnetic and tilt rod-fuzed antitank mines. It consists of an armoured personnel carrier with a forward looking infrared imager, a finger plow or roller and a magnetic signature duplicator. The teleoperated detection vehicle follows to detect antitank mines. The purpose-built vehicle carries forward looking infrared and visible imagers, a 3 m wide, down-looking sensitive electromagnetic induction detector array and a 3 m wide down-looking ground probing radar, which scan the ground in front of the vehicle. Sensor information is combined using navigation sensors and custom navigation, registration, spatial correspondence and data fusion algorithms. Suspicious targets are then confirmed by a thermal neutron activation detector. The prototype, designed and built by Defence R&D Canada, was completed in October 1997. General Dynamics Canada delivered four production units, based on the prototype concept and technologies, to the Canadian Forces (CF) in 2002. ILDS was deployed in Afghanistan in 2003, making the system the first militarily fielded, teleoperated, multi-sensor vehicle-mounted mine detector and the first with a fielded confirmation sensor. Performance of the prototype in Canadian and independent US trials is summarized and recent results from the production version of the confirmation sensor are discussed. CF operations with ILDS in Afghanistan are described.
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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 | 0.001 | 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