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Record W2065556335 · doi:10.1302/2046-3758.35.2000280

Design and execution of clinical trials in orthopaedic surgery

2014· review· en· W2065556335 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

VenueBone and Joint Research · 2014
Typereview
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineClinical trialOrthopedic surgeryRandomized controlled trialMedical physicsAlternative medicinePhysical therapyMEDLINESurgeryInternal medicinePathology

Abstract

fetched live from OpenAlex

High-quality randomised controlled trials (RCTs) evaluating surgical therapies are fundamental to the delivery of evidence-based orthopaedics. Orthopaedic clinical trials have unique challenges; however, when these challenges are overcome, evidence from trials can be definitive in its impact on surgical practice. In this review, we highlight several issues that pose potential challenges to orthopaedic investigators aiming to perform surgical randomised controlled trials. We begin with a discussion on trial design issues, including the ethics of sham surgery, the importance of sample size, the need for patient-important outcomes, and overcoming expertise bias. We then explore features surrounding the execution of surgical randomised trials, including ethics review boards, the importance of organisational frameworks, and obtaining adequate funding. Cite this article: Bone Joint Res 2014;3:161-8.

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)0.926
metaresearch head score (Gemma)0.555
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad), Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.953
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.9260.555
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0330.005
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.986
GPT teacher head0.742
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