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Record W4210829095 · doi:10.1002/9781118522318.emst133

Membrane Terminology

2013· other· en· W4210829095 on OpenAlexaff
Michael D. Guiver, Eric M.V. Hoek, Victor Nikonenko, Volodymyr V. Tarabara, Andrew L. Zydney

Bibliographic record

Venuenot available
Typeother
Languageen
FieldChemistry
TopicChemistry and Stereochemistry Studies
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsTerminologyComputer scienceNatural language processingLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

Abstract The sections in this article are General Terms Carrier‐Mediated (Facilitated) Separations Dialysis, Nanofiltration, Ultrafiltration, and Microfiltration Separations Electrically Mediated Separations Gas, Vapor, and Pervaporation Separations Osmotic Processes Acknowledgments

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)0.001
metaresearch head score (Gemma)0.003
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: Other · Consensus signal: Other
Teacher disagreement score0.093
Threshold uncertainty score0.311

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0020.001
Scholarly communication0.0060.007
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0930.131

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 head0.013
GPT teacher head0.227
Teacher spread0.214 · 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
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
Published2013
Admission routes1
Has abstractyes

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