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Record W2171257692 · doi:10.1002/cjce.5450810116

Decreasing the Sampling Time Interval in Radioactive Particle Tracking

2003· article· en· W2171257692 on OpenAlexaffvenue
Navid Mostoufi, G. Kennedy, Jamal Chaouki

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2003
Typearticle
Languageen
FieldEngineering
TopicMineral Processing and Grinding
Canadian institutionsPolytechnique Montréal
FundersUniversity of Tehran
KeywordsTRACERTracking (education)Particle (ecology)Radioactive tracerDetectorSampling (signal processing)Interval (graph theory)Radioactive sourceStandard deviationEnvironmental scienceNuclear physicsNuclear engineeringRadiochemistryPhysicsChemistryMathematicsStatisticsEngineeringGeologyOptics

Abstract

fetched live from OpenAlex

Abstract The study of the movement of solids in multiphase reactors using radioactive particle tracking is currently limited to fairly modest particle velocities because of count‐rate limitations of the detection system. In this work, this restriction was overcome by increasing the activity of the radioactive tracer, by decreasing the sampling time interval and by modifying the particle tracking software to recognize which detectors were saturated and to use only the data from the remaining unsaturated detectors. Higher tracer activity resulted in lower standard deviation of the calculated tracer coordinates.

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)0.004
metaresearch head score (Gemma)0.015
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.016
GPT teacher head0.206
Teacher spread0.190 · 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

Citations10
Published2003
Admission routes2
Has abstractyes

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