Deducing Drop Size and Impact Velocity from Circular Bloodstains
Bibliographic record
Abstract
An experimental study was done to determine the diameter and velocity of blood drops falling on a surface by measuring the size of bloodstains they produced and counting the number of radial spines projecting from them. Bloodstains were formed by releasing drops of pig blood with a range of diameters (3.0-4.3 mm) and impact velocities (2.4-4.9 m/s), onto four different flat surfaces (glass, steel, plastic, paper) with varying roughness (0.03-2.9 microm). High-speed photography was used to record drop impact dynamics. Bloodstain diameters and the number of spines formed around the rim of stains increased with impact velocity and drop diameter. Increasing surface roughness reduced stain diameter and promoted merging of spines, diminishing their number. Equations are presented that explicitly relate drop diameter and impact velocity to measurements of stain diameter and number of spines.
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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 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".