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Record W4223449974 · doi:10.1039/d2sm00049k

Globule and fiber formation with elastin-like polypeptides: a balance of coacervation and crosslinking

2022· article· en· W4223449974 on OpenAlexafffund
Kirklann Lau, Sean E. Reichheld, Simon Sharpe, Marta Cerruti

Bibliographic record

VenueSoft Matter · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective tissue disorders research
Canadian institutionsHospital for Sick ChildrenMcGill University
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsCoacervateElastinTropoelastinElastic fiberChemistryFiberBiophysicsKineticsChemical engineeringMaterials scienceBiochemistryComposite materialOrganic chemistryBiology

Abstract

fetched live from OpenAlex

model using elastin-like polypeptides and the natural chemical crosslinker genipin, we demonstrate the strong influence of the timing and kinetics of crosslinking reaction on the coacervation, crosslinking extent, and resulting morphology of elastin. We also outline a method for analyzing elastin droplet network formation as a heuristic for measuring the propensity for elastic fiber formation. From this we show that adding crosslinker during peak coacervation dramatically increases the propensity for droplet network formation.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.191

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 head0.007
GPT teacher head0.236
Teacher spread0.229 · 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 designObservational
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

Citations7
Published2022
Admission routes2
Has abstractyes

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