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Record W2317991311 · doi:10.1021/bm4010595

Injectable, High Modulus, And Fatigue Resistant Composite Scaffold for Load-Bearing Soft Tissue Regeneration

2013· article· en· W2317991311 on OpenAlexaff
James W. S. Hayami, Stephen D. Waldman, Brian G. Amsden

Bibliographic record

VenueBiomacromolecules · 2013
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsQueen's University
Fundersnot available
KeywordsRegeneration (biology)Composite numberLoad bearingScaffoldBearing (navigation)ModulusComposite materialMaterials scienceSoft tissueBiomedical engineeringSurgeryMedicineComputer science

Abstract

fetched live from OpenAlex

High modulus, two-phase, bicontinuous scaffolds were prepared by photocross-linking an aqueous suspension of chondrocytes and N-methacrylate glycol chitosan with a hydrolyzable, hydrophobic, acrylated star-copolymer. Two acrylated star-copolymers were examined: poly(ε-caprolactone-co-d,l-lactide) (5446DLLACL) and poly(ε-caprolactone-co-trimethylene carbonate) (7030TMCCL). The scaffolds were assessed for injectability, two-phase interconnectivity, fatigue resistance, and long-term static culture behavior. The 7030TMCCL scaffolds demonstrated decreased moduli of 17% after 1 × 10(6) cycles at 30% strain and 5% after 56 days in culture, compared to the 5446DLLACL scaffolds, which exhibited decreases of 58 and 68%, respectively. The 7030TMCCL scaffolds accumulated more extracellular matrix after 56 days of culture (GAG: 20.1 ± 1, collagen: 35.5 ± 1.8 μg) compared to 5446DLLACL scaffolds (GAG: 13.2 ± 0.6, collagen: 6.2 ± 3.4 μg). Overall, the 7030TMCCL-based scaffolds were shown to be better suited for use as a load bearing soft tissue scaffold.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.563

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 head0.022
GPT teacher head0.280
Teacher spread0.258 · 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 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
Published2013
Admission routes1
Has abstractyes

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