The use of a forensic blood substitute for impact pattern area of origin estimation via three trajectory analysis programs
Bibliographic record
Abstract
This study explores the use of forensic synthetic blood substitute (FBS) for impact pattern simulation and area of origin estimation. Ten impact patterns were created at a known origin using the FBS and were analyzed by groups of undergraduate students participating in a basic bloodstain pattern analysis course. The students selected 20 upward-moving stains from their given patterns to estimate an area of origin. Three linear trajectory models – BackTrack™, Hemospat, and Sherlock – were used to estimate each pattern's area of origin. Coordinate data from each model's analysis were compared with the known origin and between programs at the x-, y-, z-coordinates, and overall. Results from this analysis yielded estimates comparable to the known. A one-way ANOVA found no significant difference between programs at the x- (p = 0.79), y- (p = 0.84), z- (p = 0.96) coordinates, and overall (p = 0.81). These results support the practical use of the FBS as an alternative to whole blood for impact pattern simulations and area of origin estimation.
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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 | 0.002 | 0.008 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".