Accuracy and Repeatability of Trajectory Rod Measurement Using Laser Scanners
Bibliographic record
Abstract
Three-dimensional (3D) technologies contribute greatly to bullet trajectory analysis and shooting reconstruction. There are few papers which address the errors associated with utilizing laser scanning for bullet trajectory documentation. This study examined the accuracy and precision of laser scanning for documenting trajectory rods in drywall for angles between 25° and 90°. The inherent error range of 0.02°-2.10° was noted while the overall error for laser scanning ranged between 0.04° and 1.98°. The inter- and intraobserver errors for trajectory rod placement and virtual trajectory marking showed that the range of variation for rod placement was between 0.1°-1° in drywall and 0.05°-0.5° in plywood. Virtual trajectory marking accuracy tests showed that 75% of data values were below 0.91° and 0.61° on azimuth and vertical angles, respectively. In conclusion, many contributing factors affect bullet trajectory analysis, and the use of 3D technologies can aid in reduction of errors associated with documentation.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".