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Record W2011116076 · doi:10.3138/ptc.2011-16

Reliability of the Jones Patellofemoral Osteoarthritis Score for Radiological Assessment of Patellofemoral Degenerative Changes: Comparing a Physiotherapist to Doctors

2012· article· en· W2011116076 on OpenAlexvenueno aff
Toby O. Smith, Seung-Hee Kang, W.B. De Sprenger Rover, N. P. Walton

Bibliographic record

VenuePhysiotherapy Canada · 2012
Typearticle
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePhysical therapyOrthopedic surgeryRadiological weaponOsteoarthritisTriageReliability (semiconductor)Surgery

Abstract

fetched live from OpenAlex

PURPOSE: Radiological measurement scores are used by orthopaedic physiotherapists in triage and surveillance of patients with degenerative changes of the tibiofemoral and patellofemoral joints. The purpose of this study was to estimate the intra- and inter-observer reliability of a radiological measurement score to assess patellofemoral joint osteoarthritis, the Jones Patellofemoral Osteoarthritis Score (JPOS), with an orthopaedic physiotherapist and three grades of junior surgeons/doctors. METHODS: A total of 390 skyline X-rays of the patellofemoral joint were reviewed on 2 occasions, 4 weeks apart, by an orthopaedic physiotherapist, 2 orthopaedic surgeons, and an orthopaedic doctor. Intra- and inter-observer reliability of the JPOS was calculated using a weighted kappa analysis. RESULTS: The results indicated that while there was good overall intra-observer agreement for this measurement score for all assessors, inter-observer reliability was generally poor between the orthopaedic physiotherapist and the orthopaedic surgeons/doctor. CONCLUSION: Our findings call into question the use of the JPOS by orthopaedic physiotherapists working in triage or orthopaedic surveillance programmes with other orthopaedic clinicians.

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)0.009
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.044
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.027
GPT teacher head0.271
Teacher spread0.244 · 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 designObservational
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

Citations1
Published2012
Admission routes1
Has abstractyes

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