MétaCan
Menu
Back to cohort
Record W2048122098 · doi:10.1002/term.25

Ultra-rapid engineered collagen constructs tested in anin vivo nursery site

2007· article· en· W2048122098 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

VenueJournal of Tissue Engineering and Regenerative Medicine · 2007
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsMcGill University
Fundersnot available
KeywordsIn vivoBiomaterialTissue engineeringBiomedical engineeringChemistryCellCell biologyBiophysicsMaterials scienceBiologyBiochemistryMedicine

Abstract

fetched live from OpenAlex

Collagen is a naturally occurring structural protein, highly conserved across species. Conventionally, tissue engineering aims to convert cell-seeded constructs into a tissue-like architecture with biomimetic function. However, cell-mediated remodelling of biomaterial scaffolds in vitro has proved to be slow, costly and difficult to control. We have recently developed a novel process for ultra-rapid engineering of tissue-like constructs without the need for cell-based remodelling. Using plastic compression of type I collagen gels, the densities of collagen and cells together with mechanical properties can be brought controllably to near-tissue levels in minutes rather than weeks/months. We have now implanted these constructs in a test site across intercostal spaces in a rabbit model designed to provide cyclical tensile loading in vivo, to test their integration, cell ingrowth and angiogenic response over 5 weeks. Post-implanted constructs were recovered and tested for host vascularization, inflammatory response and mechanical integrity.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.079
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.008
GPT teacher head0.225
Teacher spread0.217 · 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