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Record W2059614124 · doi:10.1002/mabi.201290036

Macromol. Biosci. 10/2012

2012· article· it· W2059614124 on OpenAlexaff
Shahed Al‐Haque, Jason W. Miklas, Nicole Feric, Loraine L. Y. Chiu, Wen Li Kelly Chen, Craig A. Simmons, Milica Radisic

Bibliographic record

VenueMacromolecular Bioscience · 2012
Typearticle
Languageit
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCover (algebra)ElongationBiophysicsStiffnessSubstrate (aquarium)Cardiac cellChemistryNanotechnologyMaterials scienceBiologyCell biologyEngineeringEcologyComposite materialUltimate tensile strengthMechanical engineering

Abstract

fetched live from OpenAlex

Cover: The ability of cardiac fibroblasts to sense the topography of their microenvironment varies with substrate stiffness. Stiffness and topography have an interactive effect on cell morphology and alignment. This paper demonstrates that 18 kPa topographically modified substrates optimally induce elongation and alignment of cardiac fibroblasts. Further details can be found in the article by S. Al-Haque, J. W. Miklas, N. Feric, L. L. Y. Chiu, W. L. K. Chen, C. A. Simmons, and M. Radisic* on page 1342.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.369
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0120.018

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 head0.012
GPT teacher head0.265
Teacher spread0.253 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2012
Admission routes1
Has abstractyes

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