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Record W2156602676 · doi:10.1002/aic.10768

On the design of crystallization‐based separation processes: Review and extension

2006· article· en· W2156602676 on OpenAlexfundno aff
Luís A. Cisternas, Cristian M. Vásquez, Ross E. Swaney

Bibliographic record

VenueAIChE Journal · 2006
Typearticle
Languageen
FieldMaterials Science
TopicCrystallization and Solubility Studies
Canadian institutionsnot available
FundersComisión Nacional de Investigación Científica y TecnológicaBayer Canada
KeywordsCrystallizationDiagramExtension (predicate logic)Separation (statistics)Data flow diagramIdentification (biology)Computer scienceProcess engineeringMathematicsAlgorithmEngineering drawingEngineeringSystems engineeringChemical engineeringStatisticsMachine learningProgramming language

Abstract

fetched live from OpenAlex

Abstract An analysis is given of various aspects of the design of crystallization‐based separation processes. A literature review is included for each of the different themes treated in the study. Special emphasis is placed on the usefulness of the relative composition diagram as a tool for identification of possible flow sheets for separations based on fractional crystallization. A series of rules are derived that may be of practical value in the use of the relative composition diagram. Illustrative examples are included that present the advantages and limitations of this methodology. Results are compared with those obtained from the literature where available. © 2006 American Institute of Chemical Engineers AIChE J, 2006

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.004
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
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 head0.038
GPT teacher head0.297
Teacher spread0.260 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations51
Published2006
Admission routes1
Has abstractyes

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