MétaCan
Menu
Back to cohort
Record W2749243691 · doi:10.1080/15583724.2017.1364765

Microencapsulation by<i>in situ</i>Polymerization of Amino Resins

2017· article· en· W2749243691 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

VenuePolymer Reviews · 2017
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsWestern University
Fundersnot available
KeywordsIn situ polymerizationMaterials sciencePolymerizationCoatingMelamineIn situMicrometerBranching (polymer chemistry)NanotechnologyChemical engineeringComposite materialPolymerOrganic chemistryChemistryMechanical engineering

Abstract

fetched live from OpenAlex

By surrounding small droplets with a coating, one can obtain micrometer-size capsules (microcapsules), and combine multiple properties into a single system. This technology has allowed the design of advanced and functional materials. Amino resins are composed principally of urea and/or melamine and formaldehyde, and exhibit advantages as wall-forming materials, such as high mechanical strength and chemical resistance. In this review, a general description of the encapsulation process by in situ polymerization of amino resins is given. Characterization methods, and the influence of the physical and design parameters are discussed. A mechanistic description and some of the promising avenues of research are also presented.

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 score0.119
Threshold uncertainty score0.607

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 head0.028
GPT teacher head0.292
Teacher spread0.265 · 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