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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".