A Blind Trial Evaluation of a Crime Scene Methodology for Deducing Impact Velocity and Droplet Size from Circular Bloodstains<sup>*</sup>
Bibliographic record
Abstract
In a previous study, mechanical engineering models were utilized to deduce impact velocity and droplet volume of circular bloodstains by measuring stain diameter and counting spines radiating from their outer edge. A blind trial study was subsequently undertaken to evaluate the accuracy of this technique, using an applied, crime scene methodology. Calculations from bloodstains produced on paper, drywall, and wood were used to derive surface-specific equations to predict 39 unknown mock crime scene bloodstains created over a range of impact velocities (2.2-5.7 m/sec) and droplet volumes (12-45 microL). Strong correlations were found between expected and observed results, with correlation coefficients ranging between 0.83 and 0.99. The 95% confidence limit associated with predictions of impact velocity and droplet volume was calculated for paper (0.28 m/sec, 1.7 microL), drywall (0.37 m/sec, 1.7 microL), and wood (0.65 m/sec, 5.2 microL).
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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 | 0.016 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".