Manifestation of <scp>TASER</scp> drive stun burn marks on fabrics
Bibliographic record
Abstract
The TASER® is a type of conducted energy weapon (CEW) used with increasing frequency by law enforcement to subdue subjects in circumstances where compliance is necessary. When operated in the drive stun method of deployment, the electrodes at the head of this CEW are intended to make direct contact with a surface, generating heat and light which may result in burn marks as a by-product of the electrical discharge that occurs. This research aims to tackle a crucial gap in CEW research that fails to address the appearance of burn marks on fabrics. A drive stun duration (DSD) of 1, 3, and 5 s was used with three TASER models (X26P, X2, & TASER 7) on three fabrics (white 100% cotton, 100% polyester, 35:65 cotton-polyester blend) with an underlying backing of pork hock. Using a Keyence VHX-6000 confocal microscope, high magnification images were taken to observe any qualitative changes to the fabric. On polyester fabric, with increasing DSD, darker brown discoloration occurred. Additionally, on polyester fabric, the spatial orientation of the burn marks corresponded with that of the electrodes at the muzzle of each TASER model. These features enabled the correct identification of the TASER model and DSD on polyester fabric in the blind tests performed. Evidence of burn marks on cotton and blend fabrics were both limited and inconsistent such that no features were sufficiently unique to link them to any TASER model or DSD. Despite this, overall features such as discoloration and the formation of holes on these fabric types may be sufficiently unique to suggest the use of a CEW.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".