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Record W2221277184 · doi:10.11113/jt.v77.5455

WATER TREATMENT PERFOMANCE: APPLICATION OF ELECTROSPUN NANOFIBERS

2015· article· en· W2221277184 on OpenAlexaff
Agung Mataram, Ahmad Fauzi Ismail, Erna Yuliwati, Takeshi Matsuura, Ahmad Zamheri, Samsul Rizal

Bibliographic record

VenueJurnal Teknologi · 2015
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsElectrospinningMembraneMicrofiltrationNanofiberFiltration (mathematics)Materials sciencePermeability (electromagnetism)Water treatmentChemical engineeringComposite materialChemistryEnvironmental engineeringEnvironmental sciencePolymerEngineeringMathematics

Abstract

fetched live from OpenAlex

The aim of this study was to evaluate the use of nanofiber microfiltration membranes, spun by an innovative electrospinning technique, in water filtration applications. This study bridges between developments in electrospinning techniques for the production of flat sheet membranes and the application of these membranes in water filtration. The functionalized or non-functionalized for the removal of pathogens was investigated, in term of culture mechanism of bacteria spot in the waste water. Physical properties such as clean water permeability (CWP) and strength were also examined. The test showed that the electrospun membranes can be used for water filtration applications.

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 score0.024
Threshold uncertainty score0.695

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)0.0000.001

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 head0.018
GPT teacher head0.272
Teacher spread0.254 · 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

Citations8
Published2015
Admission routes1
Has abstractyes

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