Aardvark Mark IV Joint Services Flail Unit Capabilities Demonstration
Bibliographic record
Abstract
The Aardvark Clear Mine, Limited (a private British company) of Scotland has been designing and producing a variety of mechanical minefield clearance machines for seventeen (17) years. The Mark IV Joint Services Flail Unit (MKIV, see picture 1 on the next page) has been in production since 1999, and it is the product of years of improvement to the Aardvark Flail System basic design. Improvements affect engine performance, flail depth, flail control, steering control, operator safety, operator comfort, navigation and maintenance. The steering control (dual steering) can be switched from the operator (in the left seat) to the operator (in the right seat) and vice versa. Because the MKIV creates dust and works in many hostile environments, Mark IV Joint Services Flail Unit Page 2 Capabilities Demonstration Report dual steering is fitted as an aid the operators. The dual steering limits wind direction problems and downtime. During mine clearing operations, the MKIV can clear heavy brush and trees with a diameter of up to 15cm. The MKIV has been purchased by the countries of Canada, Jordan and South Korea. The information in this report is strictly based on the capabilities demonstration and not on a technical evaluation of this technology.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.083 | 0.019 |
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".