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Record W2169781512 · doi:10.4061/2011/578952

The Use of Structural Allograft in Primary and Revision Knee Arthroplasty with Bone Loss

2011· article· en· W2169781512 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvances in Orthopedics · 2011
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsMedicineSurgeryProsthesisArthroplastyBone cementTotal knee arthroplastyCement

Abstract

fetched live from OpenAlex

Bone loss around the knee in the setting of total knee arthroplasty remains a difficult and challenging problem for orthopaedic surgeons. There are a number of options for dealing with smaller and contained bone loss; however, massive segmental bone loss has fewer options. Small, contained defects can be treated with cement, morselized autograft/allograft or metal augments. Segmental bone loss cannot be dealt with through simple addition of cement, morselized autograft/allograft, or metal augments. For younger or higher demand patients, the use of allograft is a good option as it provides a durable construct with high rates of union while restoring bone stock for future revisions. Older patients, or those who are low demand, may be better candidates for a tumour prosthesis, which provides immediate ability to weight bear and mobilize.

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.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.255
Teacher spread0.236 · 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