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Record W1971639451 · doi:10.1002/app.31108

The art of surface modification of synthetic polymeric membranes

2009· article· en· W1971639451 on OpenAlex

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

VenueJournal of Applied Polymer Science · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMembraneBiofoulingSurface modificationMaterials sciencePolymerGraftingPolymeric membraneSynthetic membraneChemical engineeringPolymer chemistryPolymer scienceNanotechnologyChemistryComposite materialEngineering

Abstract

fetched live from OpenAlex

Abstract The development in the area of surface modification of polymeric synthetic membranes since 2000 is reviewed. Many patents, articles, and reviews have been written on the development in the area of surface modification of polymeric synthetic membranes subjected to RO, UF, NF, gas separation (GS), and biomedical applications, mainly since 2000, but recently more attention has been given to the modification of their surfaces to obtain desirable results. In particular, most emphasis has been given to plasma treatment, grafting of polymers on the surface, and modifying the surfaces by adding SMMs (surface‐modifying molecules). New additives are synthesized to make the polymeric membrane surfaces either to be more hydrophilic or hydrophobic, aimed at improvement in selectivity and permeability of the membranes for GS, NF, and RO. Improvement in antifouling by surface modification is also a popular topic in the membrane industries. In the last 8 years, tremendous research efforts have been made on the development of antifouling membranes. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2010

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.011
GPT teacher head0.244
Teacher spread0.234 · 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