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Record W4386132797 · doi:10.1002/9781119261728.ch8

Cruciate Ligament Matrix Metabolism and Development of Laxity

2017· other· en· W4386132797 on OpenAlexaboutno aff
Eithne Comerford

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsnot available
Fundersnot available
KeywordsAnterior cruciate ligamentExtracellular matrixCruciate ligamentMatrix metalloproteinaseLigamentMatrix (chemical analysis)AnatomyChemistryMedicineBiochemistry

Abstract

fetched live from OpenAlex

Cruciate ligaments are comprised of cells and extracellular matrix (ECM). The mechanical properties of cruciate ligaments are dependent on the composition and structure of the ECM, in particular collagen. Ligament metabolism may affect ligament strength, and it has been suggested that upregulated anterior cruciate ligament (ACL) remodeling may predispose women to ACL injury. Hormonal factors have been shown to play an important role in ligament metabolism and increased anterior knee laxity. ECM metabolism in ruptured canine cranial cruciate ligaments (CrCLs) has been investigated. Ruptured CrCLs had significantly higher amounts of immature crosslinks, total and sulfated glycosoaminoglycans (GAGs), and water content, compared with that of the intact ligaments. Increased collagen degradation, as indicated by the high levels of matrix metalloproteinases (MMP-2), is consistent with the thermal properties of the collagenous matrix of the Labrador CrCL, as well as the increased stifle joint laxity within this breed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.313
Teacher spread0.297 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2017
Admission routes1
Has abstractyes

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