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Record W3049758648 · doi:10.5435/jaaos-d-20-00266

Cartilage Injury in the Knee: Assessment and Treatment Options

2020· review· en· W3049758648 on OpenAlexaff
Aaron J. Krych, Daniël B.F. Saris, Michael J. Stuart, Brittney Hacken

Bibliographic record

VenueJournal of the American Academy of Orthopaedic Surgeons · 2020
Typereview
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsObject Research Systems (Canada)
Fundersnot available
KeywordsChondroplastyMedicineCartilageSurgeryAutologous chondrocyte implantationChondrocyteMeniscusOsteoarthritisArticular cartilageArthroplastyAnatomyKnee replacementPathology

Abstract

fetched live from OpenAlex

Cartilage injuries in the knee are common and can occur in isolation or in combination with limb malalignment, meniscus, ligament, and bone deficiencies. Each of these problems must be addressed to achieve a successful outcome for any cartilage restoration procedure. If nonsurgical management fails, surgical treatment is largely based on the size and location of the cartilage defect. Preservation of the patient's native cartilage is preferred if an osteochondral fragment can be salvaged. Chondroplasty and osteochondral autograft transfer are typically used to treat small (<2 cm) cartilage defects. Microfracture has not been shown to be superior to chondroplasty alone and has potential adverse effects, including cyst and intralesional osteophyte formation. Osteochondral allograft transfer and matrix-induced autologous chondrocyte implantation are often used for larger cartilage defects. Particulated juvenile allograft cartilage is another treatment option for cartilage lesions that has good to excellent short-term results but long-term outcomes are lacking.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.568

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.038
GPT teacher head0.381
Teacher spread0.343 · 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 designOther design
Domainnot available
GenreReview

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

Citations172
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Academy of Orthopaedic SurgeonsSame topicKnee injuries and reconstruction techniquesFrench-language works237,207