MétaCan
Menu
Back to cohort
Record W2014820269 · doi:10.1520/jfs2003224

Deducing Drop Size and Impact Velocity from Circular Bloodstains

2004· article· en· W2014820269 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Forensic Sciences · 2004
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer Centre
Fundersnot available
KeywordsDrop (telecommunication)Materials scienceDrop impactSurface roughnessComposite materialSurface finishOpticsMineralogyMechanicsChemistryPhysicsEngineering

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.621
Threshold uncertainty score0.253

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.236
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it