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Record W2514169052 · doi:10.1021/acs.iecr.5b00915

Reaction Monitoring of in Situ Formation of Poly(sodium acrylate)-Based Nanocomposites Using ATR-FTIR Spectroscopy

2015· article· en· W2514169052 on OpenAlexafffund
Samaneh Khanlari, Marc A. Dubé

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2015
Typearticle
Languageen
FieldMaterials Science
TopicThermal and Kinetic Analysis
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFourier transform infrared spectroscopyAttenuated total reflectionIn situNanocompositeAcrylateMonomerMaterials scienceGravimetric analysisPolymerChemistryNuclear chemistryPolymer chemistryAnalytical Chemistry (journal)Chemical engineeringChromatographyOrganic chemistryNanotechnologyComposite material

Abstract

fetched live from OpenAlex

The in situ formation of poly(sodium acrylate)-based nanocomposites was monitored in-line using an attenuated total reflectance/Fourier transform infrared (ATR-FTIR) spectroscopic probe. Results were compared with conversion measurements using an off-line gravimetric method. A multivariate statistical data treatment based on the online data for the nanocomposite containing 0.5 wt % of nanosilver was used to calibrate the ATR-FTIR spectroscopic probe. The ATR-FTIR method was shown to be reliable based on 95% confidence intervals for monitoring the production of polymers synthesized in the presence of different amounts of nanosilver over the full range of monomer conversion.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.105
GPT teacher head0.342
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), 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

Citations13
Published2015
Admission routes2
Has abstractyes

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