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Record W3157467923 · doi:10.1039/d1bm00402f

Thermally driven formation of polyphenolic carbonized nanogels with high anticoagulant activity from polysaccharides

2021· article· en· W3157467923 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

VenueBiomaterials Science · 2021
Typearticle
Languageen
FieldEngineering
TopicGraphene and Nanomaterials Applications
Canadian institutionsUniversité de Montréal
FundersMinistry of Science and Technology, Taiwan
KeywordsNanosheetChemistryPolyphenolCarbonizationCoagulationAmphiphileChemical engineeringNanotechnologyMaterials scienceOrganic chemistryPolymerAdsorptionCopolymer

Abstract

fetched live from OpenAlex

M] toward thrombin. In addition, the thrombin clotting time delay caused by the GNS/Alg-NGs is 10-fold longer than that of natural polyphenolic compounds, such as quercetin, catechin, naringenin, caffeic acid, and ferulic acid. The thrombin- or kaolin-activated thromboelastography of whole-blood coagulation reveals that the GNS/Alg-NGs display a much stronger anticoagulant ability than that of untreated alginate and naturally sulfated polysaccharides (fucoidan). The GNS/Alg-NGs exhibit superior biocompatibility and anticoagulant activity, as observed with an in vivo rat model, revealing their potential as a blood thinner for the treatment of thrombotic disorders.

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 score0.030
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.207
Teacher spread0.197 · 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