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Record W2559869609 · doi:10.1002/cssc.201601372

“Practical” Electrospinning of Biopolymers in Ionic Liquids

2016· article· en· W2559869609 on OpenAlexaff
Julia L. Shamshina, Oleksandra Zavgorodnya, Jonathan R. Bonner, Gabriela Gurău, Thomas Di Nardo, Robin D. Rogers

Bibliographic record

VenueChemSusChem · 2016
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsMcGill University
FundersNuclear Energy University Program
KeywordsIonic liquidElectrospinningChitinNanoscopic scaleChemical engineeringIonic bondingMaterials scienceNanofiberNanotechnologyShrimpChemistryPolymer chemistryOrganic chemistryPolymerChitosanIonComposite materialCatalysis

Abstract

fetched live from OpenAlex

Abstract To address the need to scale up technologies for electrospinning of biopolymers from ionic liquids to practical volumes, a setup for the multi‐needle electrospinning of chitin using the ionic liquid 1‐ethyl‐3‐methylimidazolium acetate, [C 2 mim]‐[OAc], was designed, built, and demonstrated. Materials with controllable and high surface area were prepared at the nanoscale using ionic‐liquid solutions of high‐molecular‐weight chitin extracted with the same ionic liquid directly from shrimp shells.

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 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 score0.007
Threshold uncertainty score0.704

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 head0.015
GPT teacher head0.296
Teacher spread0.281 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations54
Published2016
Admission routes1
Has abstractyes

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