Empirical investigation of passive blood drop trajectory and first point of contact on inclined surfaces
Bibliographic record
Abstract
The first point of contact between a spherical blood drop and a surface is related to the angle between the trajectory of the blood drop and the surface being struck. This angle is often referred to as the impact angle which can be estimated by knowing the width and length of the resultant elliptical bloodstain. Most software programs dedicated to area of origin analysis indicate the location of the backtracked bloodstain trajectory to be at the geometric centre or at the tip of the bloodstain ellipse. However, it is unknown how the first point of contact and the blood drop trajectory (here defined as the locus of the centre of mass of the drop as it travels) are related empirically. Thus, this study aims to look at how the initial point of contact and the trajectory at the impact of a blood drop relates to the formed bloodstain ellipse. Two volumes of blood (0.013 ml and 0.071 ml) were dropped from a height of 10 cm and 40 cm onto an inclined surface at 0°, 15°, 30°, 45°, 60°, and 75°. The transition from a spherical blood drop to an elliptically shaped bloodstain was recorded using a high-speed camera for all tests. A total of 72 ellipses were analyzed to determine the location of the first point of contact and trajectory point of the blood drop and how they relate to the formed elliptical bloodstain. A relationship was found between the first point of contact and the bloodstain trajectory which was dependent on the impact angle. However, there were clear deviations from theoretical assumptions due to blood drop oscillations, the effects of gravity, and the natural fluid characteristics of blood. The results of this study may assist bloodstain pattern analysts and software developers by more accurately applying the location of the blood drop trajectory based on empirical data.
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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 | 0.001 | 0.010 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".