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Size Enlargement

2000· other· en· W4230654046 on OpenAlexaff
C.E. Capes, K. Darcovich

Bibliographic record

VenueKirk-Othmer Encyclopedia of Chemical Technology · 2000
Typeother
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsGranulationAgglomerateEconomies of agglomerationCompactionPelletizingExtrusionMaterials scienceParticle sizeParticle (ecology)Granular materialWettingProcess engineeringNanotechnologyChemical engineeringComposite materialPelletsGeologyEngineering

Abstract

fetched live from OpenAlex

Abstract Size enlargement concerns those processes which bring together fine powder particles into larger masses to improve the properties of the powders. Many diverse industries benefit from size enlargement processes. Examples discussed herein include fertilizer granulation, iron ore pelletization, tablet feeds for pharmaceuticals, instant food products, and the processing of mineral and chemical products. This article considers primarily those processes in which the creation of coarse granular material from fines is the objective. The characteristics of individual agglomerates are important only in their effect on the properties of the bulk granular product. Following initial discussion of particle‐bonding mechanisms and the theory and measurement of agglomerate strength, size enlargement processes and equipment, including principal design parameters, are described. These processes are considered on the basis of the principal mechanism used to bring the particles together into agglomerates. The categories used are agglomeration by tumbling and other agitation methods, pressure compaction and extrusion methods, heat reaction, fusion, and drying methods, and agglomeration from liquid suspensions by competitive wetting.

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 categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.265
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.003
GPT teacher head0.187
Teacher spread0.185 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2000
Admission routes1
Has abstractyes

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Same venueKirk-Othmer Encyclopedia of Chemical TechnologySame topicGranular flow and fluidized bedsFrench-language works237,207