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Record W2106361359 · doi:10.1002/pat.3606

Fabrication of fibrous patterned architectures with controlled deposition and multidirectional alignment

2015· article· en· W2106361359 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

VenuePolymers for Advanced Technologies · 2015
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsElectrospinningFabricationMaterials scienceDeposition (geology)NanotechnologyElectrodeMicroprocessorPolymerComputer scienceComposite materialComputer hardware

Abstract

fetched live from OpenAlex

In recent years, the ability to produce nanofibrous patterned architectures by electrospinning has exposed a wide range of potential applications in biomedical and industrial fields. Directional alignment, controlled deposition, and density variation into the patterns are desirable for many applications such as tissue engineering scaffolds and micro/nano‐electronic devices. In this study, we introduce a versatile method for fabrication of various kinds of nanofibrous deposition patterns with the help of microprocessor based control system for switching collector electrodes. By controlling the concurrent activation time of two adjacent electrodes, we demonstrated that amount of fibers going into the pattern can be adjusted and alignment in electrospun fibers can be obtained. We also revealed that the deposition density of electrospun fibers in different areas of patterned architectures can be varied. This advanced technique can have a significant impact in enhancing the technology of electrospinning and can help develop new applications in health sciences and industrial sectors. Copyright © 2015 John Wiley & Sons, Ltd.

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 score0.183
Threshold uncertainty score0.339

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 head0.009
GPT teacher head0.250
Teacher spread0.241 · 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