Field Evaluation of the Mine Hammer: A Landmine Neutralization Mechanism
Bibliographic record
Abstract
An antipersonnel landmine neutralizing mechanism, called the Mine Hammer, was designed with a prototype developed by the Agriculture and Bioresource Engineering Department, University of Saskatchewan and Defence Research and Development Canada -- Suffield. The Mine Hammer technology combined flail mechanisms and agriculture tillage interaction mechanics. The prototype was retrofitted to be powered by a 78.4 kW tractor and was field evaluated in August 2002. The test plots represented gravel road, prairie clay soil with stubble and full stand of Kochia weed for vegetation and simulated tree stump terrains. Dummy or mechanical replicas of antipersonnel landmines were placed at 0, 25, 50, 100 and 200mm depths. The Mine Hammer triggered and/or fragmented the replica landmines. Its mechanical neutralization effectiveness over the five test plots was 97%. The Mine Hammer produced a two layer overburden consisting of a loose till above a dense, compact soil layer. Non-neutralized mine replicas were buried within the compact layer and were not triggered when subjected to loads from human footsteps, jumping and stomping.
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.
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 | 0.002 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".