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Record W2011150752 · doi:10.1016/j.eats.2014.10.002

Arthroscopic Treatment of Hip Chondral Defects With Bone Marrow Stimulation and BST‐CarGel

2015· article· en· W2011150752 on OpenAlexaboutno aff
Marc Tey, Xavier Pelfort, Joan Carles Monllau

Bibliographic record

VenueArthroscopy Techniques · 2015
Typearticle
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSurgeryLesionBone marrowBlood lossWound healingPathology

Abstract

fetched live from OpenAlex

Microfracture, the current standard of care for the treatment of non-degenerative chondral lesions in the hip joint, is limited by the poor quality of the filling fibrocartilaginous tissue. BST-CarGel (Piramal Life Sciences, Laval, Quebec, Canada) is a chitosan-based biopolymer that, when mixed with fresh, autologous whole blood and placed over the previously microfractured area, stabilizes the blood clot and enhances marrow-triggered wound-healing repair processes. BST-CarGel has been previously applied in the knee, with statistically significant greater lesion filling and superior repair tissue quality compared with microfracture treatment alone. In this report we describe the application of BST-CarGel for the arthroscopic treatment of hip chondral lesions. Our preliminary data suggest that our BST-CarGel procedure provides high-quality repair tissue and therefore may be considered a safe, cost-efficient therapeutic choice for the treatment of hip chondral defects.

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 score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.024
GPT teacher head0.308
Teacher spread0.284 · 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

Citations23
Published2015
Admission routes1
Has abstractyes

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