MétaCan
Menu
Back to cohort
Record W2268126590 · doi:10.1002/prep.201500262

Measurement of Particle Density During Explosive Particle Dispersal

2015· article· en· W2268126590 on OpenAlexaff
Samuel Goroshin, David L. Frost, Robert C. Ripley, Fan Zhang

Bibliographic record

VenuePropellants Explosives Pyrotechnics · 2015
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsDefence Research and Development CanadaMartec (Canada)McGill University
Fundersnot available
KeywordsExplosive materialParticle (ecology)Materials scienceSootAttenuationGauge (firearms)LaserOpticsPhysicsMolecular physicsCombustionChemistryGeology

Abstract

fetched live from OpenAlex

Abstract A gauge based on laser light attenuation has been developed to determine the temporal history of particle number density during the explosive dispersal of inert particles. The optical scheme of the gauge employs narrow band pass and spatial optical filters that protect the optical sensors from ambient light and laser light scattered by particles. The gauge is used in field experiments to measure particle density at two locations in close proximity to spherical metalized explosive charges containing a packed bed of either iron, nickel, or glass particles saturated with nitromethane. The heavy iron particles penetrate the blast wave in the near field, whereas the lighter particles remain behind the blast wave. Comparisons with multiphase calculations indicate that the particle density field inferred from the light intensity signals is consistent with the computations until the point at which the combustion products containing soot arrives at the gauge, blocking the laser light.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.231
Teacher spread0.182 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2015
Admission routes1
Has abstractyes

Explore more

Same venuePropellants Explosives PyrotechnicsSame topicCombustion and Detonation ProcessesFrench-language works237,207