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Record W2142881435 · doi:10.1002/marc.200700359

Molecularly Imprinted Nanofiber Membranes from Carboxylated Polysulfone by Electrospray Deposition

2007· article· en· W2142881435 on OpenAlex
Masakazu Yoshikawa, Koji Nakai, Hidetoshi Matsumoto, Akihiko Tanioka, Michael D. Guiver, Gilles P. Robertson

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

VenueMacromolecular Rapid Communications · 2007
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMembranePolysulfoneNanofiberElectrosprayChemical engineeringElectrospinningMaterials scienceMolecular imprintingMolecularly imprinted polymerPolymer chemistryPolymerChemistryChromatographySelectivityOrganic chemistryNanotechnologyMass spectrometryBiochemistry

Abstract

fetched live from OpenAlex

Abstract It is demonstrated that polymeric materials can be directly converted into molecular (chiral) recognition nanofiber membranes by simultaneously applying an electrospray deposition and an alternative molecular imprinting during the membrane preparation process. Polysulfone with a degree of substitution of 0.88 was adopted as the candidate polymeric material for molecularly imprinted nanofiber membranes. Molecularly imprinted nanofiber membranes imprinted by Z ‐ D ‐Glu recognize the D ‐isomer in preference to the corresponding L ‐isomer and vice versa. The amino acid preferentially incorporated into the membrane is selectively permeated through the membrane by using a concentration gradient as a driving force for membrane transport. magnified image

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.573
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.246
Teacher spread0.239 · 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