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Record W2072830554 · doi:10.1002/cvde.200706616

Multi‐scale Modeling and Constrained Sensitivity Analysis of Particulate CVD Systems

2007· article· en· W2072830554 on OpenAlex
C. M. White, G. Zeininger, Paul E. Ege, B. Erik Ydstie

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

VenueChemical Vapor Deposition · 2007
Typearticle
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsProcess Research Ortech (Canada)
Fundersnot available
KeywordsEconomies of agglomerationDiscretizationBreakageSensitivity (control systems)PopulationNucleationFluidized bedMechanicsExpression (computer science)Scale (ratio)Biological systemMathematicsMaterials scienceEnvironmental scienceStatistical physicsComputer sciencePhysicsEngineeringThermodynamicsMathematical analysisChemical engineering

Abstract

fetched live from OpenAlex

Abstract A finite‐dimensional, state‐space model of the discrete distribution function bypasses discretization of the continuous population balance, and facilitates simple modeling and fast numerical integration. An analytical expression describes the steady‐state, average particle diameter as a function of parameters such as nucleation, agglomeration, breakage, seed rate, and average seed particle diameter. The discrete population balance model is used to evaluate the analytical expression sensitivity to growth and decay phenomena such as nucleation, agglomeration, and breakage. The analytical expression is validated against data obtained from an industrial‐scale, fluidized bed, pilot reactor designed to produce solar‐grade silicon. The results indicate how the analytical expression describes a CVD‐type growth process, and also how the growth process may deviate due to the operating conditions.

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 score0.555
Threshold uncertainty score0.353

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 head0.014
GPT teacher head0.220
Teacher spread0.206 · 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