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Record W2337880403 · doi:10.2106/jbjs.n.01079

Humeral Head Arthroplasty and Meniscal Allograft Resurfacing of the Glenoid

2015· article· en· W2337880403 on OpenAlexaff
Aaron J. Bois, Ian J. Whitney, Jeremy S. Somerson, Michael A. Wirth

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2015
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineShouldersSurgeryRadiographyElbowArthroplastySubluxationVisual analogue scale

Abstract

fetched live from OpenAlex

The two to five-year results of humeral head arthroplasty and lateral meniscal allograft resurfacing of the glenoid in patients fifty-five years of age or younger were previously reported by the senior author (M.A.W.). The purpose of the present study was to report the survival rate, clinical findings, and radiographic results of the original thirty shoulders (thirty patients) followed for a mean duration of 8.3 years (range, five to twelve years). The scores on the visual analog scale for pain, American Shoulder and Elbow Surgeons scoring system, and Simple Shoulder Test were significantly improved at the latest follow-up evaluation compared with the preoperative findings (p < 0.001). Radiographic indices of posterior subluxation did not significantly increase from the immediate postoperative imaging to the latest radiographs, while the glenohumeral joint space demonstrated a gradual decrease. Nine (30%) of thirty shoulders were known to have undergone a reoperation. The present study demonstrated that biological glenoid resurfacing combined with hemiarthroplasty can provide significant improvement in shoulder function and pain relief in young patients with glenohumeral arthritis; however, mid-term follow-up at a mean of over eight years demonstrated a high reoperation rate.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
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 head0.071
GPT teacher head0.295
Teacher spread0.224 · 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

Citations24
Published2015
Admission routes1
Has abstractyes

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