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Record W1965130919 · doi:10.1097/bot.0b013e3181b7eae7

The Use Osteochondral Allograft in the Treatment of a Severe Femoral Head Fracture

2010· article· en· W1965130919 on OpenAlexaff
Markku Nousiainen, Milan Sen, Douglas N. Mintz, Dean G. Lorich, Omesh Paul, Robert L. Buly, David L. Helfet

Bibliographic record

VenueJournal of Orthopaedic Trauma · 2010
Typearticle
Languageen
FieldMedicine
TopicBone and Joint Diseases
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineFemoral headAcetabulumMagnetic resonance imagingRadiographySurgeryOrthopedic surgeryOsteoarthritisRadiology

Abstract

fetched live from OpenAlex

This study reviews the second case in the literature involving the use of frozen osteochondral allograft to reconstruct a femoral head fracture-dislocation. The case involved significant, unreconstructable damage to the weightbearing area of the femoral head in an 18-year-old male. Clinical and diagnostic imaging follow up at 46 months revealed that despite magnetic resonance imaging and radiographic evidence of progressive arthrosis in the hip, including subchondral cystic change in the femoral head and localized cartilage loss in the acetabulum and femoral head, the patient had excellent function with no complications (Harris hip score 100, hip dysfunction and osteoarthritis outcome score 62, musculoskeletal function assesment score 22, SF-36 score 81). The use of osteochondral allograft may serve as a useful tool for the orthopaedic surgeon faced with an unreconstructable femoral head fracture-dislocation in a young patient.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.001
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 head0.037
GPT teacher head0.302
Teacher spread0.265 · 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 designCase report
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

Citations36
Published2010
Admission routes1
Has abstractyes

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