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Scrutinizing the Nanostructural and Nanomechanical Features of Regenerated Cellulose Ultrafiltration Membranes

2015· article· en· W2041946970 on OpenAlex
Luciano Paulino Silva

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Membrane and Separation Technology · 2015
Typearticle
Languageen
FieldEngineering
TopicNanopore and Nanochannel Transport Studies
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsMembraneUltrafiltration (renal)Nanoscopic scaleCelluloseAtomic force microscopyNanotechnologyForce spectroscopyMaterials scienceChemical engineeringRaman spectroscopyResolution (logic)ChemistryChromatographyComputer scienceOpticsEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Ultrafiltration (UF) membranes have been widely used for many separation processes in which high performance is required. Commercial regenerated cellulose UF membranes with variable molecular weight cut-offs were characterized by high performance atomic force microscopy (AFM) using the novel quantitative nanomechanical mapping mode and the versatility of its signal channels towards nanoscale features elucidation of the materials surface. In addition, Raman spectroscopy was applied in order to investigate some possible chemical behavior changes associated with the UF membranes’ cut-offs. Overall, the results showed that the proposed AFM method was reliable to gain qualitative and quantitative data at unprecedented nanoscale resolution and such information can be used to distinguish UF membranes according to their specific molecular weight cut-offs and properties even on situations in which the molecular behavior were not influenced by the UF membrane’ cut-off. This approach can be useful on quality control procedures of researchers and manufacturers producing or modifying these polymeric materials.

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 score0.009
Threshold uncertainty score0.296

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 head0.014
GPT teacher head0.234
Teacher spread0.220 · 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