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Record W2016681676 · doi:10.1021/ma070215u

Water-Dispersible Oil-Filled ABC Triblock Copolymer Vesicles and Nanocapsules

2007· article· en· W2016681676 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

VenueMacromolecules · 2007
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsQueen's University
Fundersnot available
KeywordsVesicleCopolymerNanocapsulesReagentSolventChemical engineeringMaterials scienceNanotechnologyChemistryOrganic chemistryPolymerNanoparticleMembrane

Abstract

fetched live from OpenAlex

Customer-engineered block copolymers can self-assemble under appropriate conditions in block-selective solvents into vesicles. Such vesicles have been of enormous academic interest over the past decade for their potential applications in enzyme encapsulation as well as in controlled release of drugs, fragrance, fertilizer, etc. A drawback with the self-assembled vesicles is that the solvent external to and in the internal cavity of a vesicle is essentially the same. This makes loading of reagents into the vesicle cavities difficult. Reported in this paper is a methodology for the one-pot synthesis of water-dispersible oil-filled ABC triblock copolymer vesicles or nanocapsules. Such a methodology achieves reagent (oil) filling and vesicle preparation simultaneously and should help commercial acceptance of block copolymer vesicles.

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 score0.049
Threshold uncertainty score0.893

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)0.0010.000

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 head0.222
Teacher spread0.215 · 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