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Recognition and Selective Transport of Nucleic Acid Components through Molecularly Imprinted Polymeric Membranes

2001· article· en· W2046806109 on OpenAlex
Masakazu Yoshikawa, Jun‐ichiro Izumi, 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 Materials and Engineering · 2001
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMembraneMolecularly imprinted polymerMolecular recognitionMolecular imprintingSelective adsorptionPolymerMoleculeMaterials scienceCombinatorial chemistrySelectivityGuanosinePolystyreneAdsorptionChemistryOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

To induce “molecular memory” in a membrane substrate at the same time that the membrane was prepared from its polymer solution, an alternative molecular imprinting technique was applied. Upon membrane formation, a “molecular memory” of the imprint molecule is retained by the formed membrane that recognizes or favors interaction with print molecule analogues. In the present study, polystyrene resin bearing a tetrapeptide derivative, a derivative of natural polymer, and an entirely non-chiral synthetic polymer were adopted as candidate materials to form molecular recognition sites. 9-Ethyladenine was adopted as a print molecule. These molecularly imprinted polymeric membranes recognized and adsorbed adenosine (As), which is an analogue of the print molecule, in preference to guanosine (Gs) from As/Gs mixtures. However Gs was permeated in preference to As contrary to adsorption selectivity, possibly because of the relatively high affinity between As and the membrane.

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 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 score0.018
Threshold uncertainty score0.936

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.016
GPT teacher head0.220
Teacher spread0.204 · 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