Canadian landmine detection research program
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
Defence R&D Canada (DRDC), an agency within the Department of National Defence, has been conducting research and development (R&D) on the detection of landmines for countermine operations and of unexploded ordnance (UXO) for range clearance since 1975. The Canadian Centre for Mine Action Technologies (CCMAT), located at DRDC Suffield, was formed in 1998 to carry out R&D related to humanitarian demining. The lead group responsible for formulating and executing both countermine and humanitarian R&D programs in detection is the Threat Detection Group at DRDC Suffield. This paper describes R&D for both programs under the major headings of remote minefield detection, close-in scanning detection, confirmation detection and teleoperated systems. Among DRDC's achievements in landmine and UXO detection R&D are pioneering work in electromagnetic and magnetic identification and classification; the first military-fielded multisensor, teleoperated vehicle-mounted landmine detection system; pioneering use of confirmation detectors for multisensor landmine detection systems; the first fielded thermal neutron activation landmine confirmation sensor; the first detection of landmines using a real-time hyperspectral imager; electrical impedance imaging detection of landmines and UXO and a unique neutron backscatter landmine imager.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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