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Record W2517044338 · doi:10.1002/macp.201600328

Microfluidic Studies of Polymer Adsorption in Flow

2016· article· en· W2517044338 on OpenAlexafffund
Alinaghi Salari, Eugenia Kumacheva

Bibliographic record

VenueMacromolecular Chemistry and Physics · 2016
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicrochannelMicrofluidicsPolymerBiofoulingNanotechnologyAdsorptionMaterials scienceFlow (mathematics)ChemistryOrganic chemistryComposite materialMechanics

Abstract

fetched live from OpenAlex

Adsorption of polymer molecules under flow conditions governs a broad range of desired or undesired phenomena and has a broad range of applications. Microfluidic platforms integrated with analytical instrumentation offer the capability to study polymer adsorption in flow in a time‐ and labour‐efficient manner. Precise control of the microchannel dimensions and flow parameters enables accurate control of shear forces imposed on polymer solutions and on the molecules deposited on the surface, along with high sensitivity, enhanced reliability, and low reagent consumption. This review highlights recent advances in theoretical and experimental microfluidic studies of polymer immobilization under flow conditions in three area, namely, biosensing, biofouling, and studies of thrombosis and hemostasis. image

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 score0.339

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 head0.011
GPT teacher head0.213
Teacher spread0.202 · 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

Citations4
Published2016
Admission routes2
Has abstractyes

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