Bibliographic record
Abstract
IntroductionAlthough land mine problems existed in many regions, Bosnia (1995) and Afghanistan (2001) gave the land mine issue a particular sense of urgency.Intended for warfare, these mines remain buried after the end of the conflict.These mines are triggered by civilians causing around 15,000-20,000 victims per year in 90 countries, ICBL (2006).The U.S. State Department estimates that there are around 40-50 million of buried mines that need to be cleared.According to Horowitz (1996) 100,000 mines are found and destroyed per year; thus 450 years will be necessary to clean all mines.However, each year, 1.9 million of new mines are buried.In addition, the presence of mines also causes economic decline being one of the major limitations to agricultural work on these regions, Cameron & Lawson (1998).Thus, it is necessary to develop new techniques which allow to detect mines quickly and with high precision.The Ottawa treaty, Ottawa (1997), banning the production and use of AP mines was signed by 158 countries in 2007 however the most important AP manufacturers, China, Russia, India and EE.UU, have not yet signed it.Nowadays more than 350 types of mines exist, Vines & Thompson (1999); but they can be broadly divided into two main categories:• Antipersonnel (AP) mines.• Antitank (AT) mines.AT mines are relative big and heavy (2-5 Kg) and are usually laid on the ground forming regular patterns and shallowly buried.AT mines have enough explosive to destroy a tank or a truck, as well as to kill people in or around the vehicle; they also require more pressure to be detonated than AP mines.On the contrary AP mines contain less explosive and are lighter than AT mines.AP mines can be buried anywhere, they may lie on the surface or be shallowly buried.Sometimes they are placed in a regular pattern to protect AT mines, however in most cases they are placed randomly.Moreover, as AP mines are light and small, wind or rain can easily move them making their location, even with the original pattern, more difficult.AP mines are designed to damage foot soldiers avoiding their penetration into an specific area.These mines can kill or disable their victims and are activated by pressure, tripwire or remote detonation.These characteristics make AT mine detection and clearance easier than AP mine detection.Detection and clearance of buried mines is a big problem with lots of humanitarian, environmental and economic implications.Current techniques for non-destructive evaluation 2 www.intechopen.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.006 |
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".