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Record W2310960062 · doi:10.1302/0301-620x.95b11.32767

I can’t get no satisfaction after my total knee replacement

2013· review· en· W2310960062 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

VenueThe Bone & Joint Journal · 2013
Typereview
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsNova Scotia HospitalDalhousie University
Fundersnot available
KeywordsPatient satisfactionArthroplastyTotal knee replacementPhysical therapyMedicineKnee replacementOutcome (game theory)Total knee arthroplastyPopulationPhysical medicine and rehabilitationSurgery

Abstract

fetched live from OpenAlex

Satisfaction is increasingly employed as an outcome measure for a successful total knee replacement (TKR). Satisfaction as an outcome measure encompasses many different intrinsic and extrinsic factors related to a person's experience before and after TKR. The Swedish Knee Arthroplasty Registry has previously demonstrated on a large population study that 17% of TKR recipients are not satisfied with their TKR outcome. This finding has been replicated in other countries. Similar significant factors emerged from these registry studies that are related to satisfaction. It would appear that satisfaction is better after more chronic diseases and whether the TKR results in pain relief or improved function. Importantly, unmet pre-operative expectations are a significant predictor for dissatisfaction following a TKR. It may be possible to improve rates by addressing the issues surrounding pain, function and expectation before embarking on surgery.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.964
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0060.004

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 head0.030
GPT teacher head0.290
Teacher spread0.260 · 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