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Record W1972000820 · doi:10.1002/ppsc.200390038

Analysis of Single Particle Attrition during Impact Experiments<sup>†</sup>

2003· article· en· W1972000820 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

VenueParticle & Particle Systems Characterization · 2003
Typearticle
Languageen
FieldEngineering
TopicMineral Processing and Grinding
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsBreakageAttritionAbrasion (mechanical)Particle (ecology)Materials scienceParticle sizeFracture (geology)Composite materialParticle-size distributionMechanicsChemistryPhysicsGeology

Abstract

fetched live from OpenAlex

Abstract Particle breakage can be characterised as attrition, chipping, fracture, abrasion and wear. All these types of breakage mechanisms are the effect of the damage caused to these particles. These mechanisms can be differentiated not just on the basis of magnitude and direction of the force but also by the damage caused to the particles. The damage is measured by change in the size distribution and the change in shape of the particles. In the current research, experiments were performed on the newly developed Repeated Impact Test. The unique feature of this test is that about hundred particles can be subjected simultaneously to a monitored number of impacts, without particle‐particle interactions at regulated velocities. The preliminary experiments were performed with single crystalline particles of different shapes and sizes. After fixed number of impacts, the images of the particles were taken. The volume and shape of the particles were determined by image analysis. It was observed that the rate of attrition was very high when the particles are irregular. The rate decreased as the particles became more spherical.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.952

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.255
Teacher spread0.228 · 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