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Knee Injury Outcomes Measures

2009· review· en· W1903986699 on OpenAlexaboutno aff
Rick W. Wright

Bibliographic record

VenueJournal of the American Academy of Orthopaedic Surgeons · 2009
Typereview
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePhysical therapyOsteoarthritisPsychological interventionAnterior cruciate ligamentOrthopedic surgeryQuality of life (healthcare)MEDLINEScale (ratio)Physical medicine and rehabilitationSurgeryAlternative medicine

Abstract

fetched live from OpenAlex

Outcomes measures have long been used in the assessment of knee injuries and management protocols. In the past decade, there has been a shift from clinician-based outcomes tools to the development and validation of patient-reported outcomes measures. General health as well as disease- and medical condition-specific outcomes measures have been so modified. The Medical Outcomes Study 36-Item Short Form is the most commonly used general health measure in orthopaedics. Joint-specific measures include the Western Ontario and McMaster Universities Osteoarthritis Index, the Knee Injury and Osteoarthritis Outcome Score, and the International Knee Documentation Committee Subjective Form. The Lysholm Knee Scale and the Cincinnati Knee Rating Scale continue to be popular, especially for the assessment of ligamentous injuries. The ACL Quality of Life score is a disease-specific, patient-reported outcomes measure of anterior cruciate ligament deficiency. The historically used Tegner activity level scale and the recently developed Marx activity level scale are used in conjunction with these outcomes measures to make possible a global assessment of recovery from knee injuries and clinician interventions.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.036
GPT teacher head0.363
Teacher spread0.328 · 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.

Study designNot applicable
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

Citations182
Published2009
Admission routes1
Has abstractyes

Explore more

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