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Record W3096919675 · doi:10.1063/12.0000861

Reaction initiation of metal spheres upon ballistic impact with an anvil

2020· article· en· W3096919675 on OpenAlexaff
Dihia Idrici, Michael Soo, Samuel Goroshin, Andrew Higgins, David L. Frost

Bibliographic record

VenueAIP conference proceedings · 2020
Typearticle
Languageen
FieldMaterials Science
TopicHigh-Velocity Impact and Material Behavior
Canadian institutionsMcGill University
Fundersnot available
KeywordsProjectileMaterials scienceLight-gas gunIgnition systemTitaniumHafniumAluminiumZirconiumSPHERESMetallurgyPhysics

Abstract

fetched live from OpenAlex

When a metallic projectile impacts an anvil at high speed, fragmentation of the projectile and ignition of the fragments may occur. In the present experimental study, small metallic spheres and cylinders are accelerated up to speeds of 1.2 km/s by a single-stage light-gas gun and impact an aluminum oxide anvil. Velocity thresholds for ignition are determined for aluminum, titanium, zirconium, and hafnium projectiles using optical diagnostics. A high-speed digital camera is utilized to observe the fragmentation process, emission spectroscopy is used to infer the temperature of the fragments, and a fast response avalanche photodetector is used to obtain the history of radiant emissions from the impact.

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 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 categoriesInsufficient payload (model declined to judge)
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 score0.057
Threshold uncertainty score1.000

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 communication0.0000.001
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 head0.294
Teacher spread0.245 · 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 teacher head, not a consensus.

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

Citations1
Published2020
Admission routes1
Has abstractyes

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