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Record W2123070324 · doi:10.2106/jbjs.h.01593

An Evidence-Based Approach to the Adoption of New Technology

2009· article· en· W2123070324 on OpenAlexaff
Henry Ahn, Mohit Bhandari, Emil H. Schemitsch

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2009
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsMcMaster UniversitySt. Michael's Hospital
Fundersnot available
KeywordsRandomized controlled trialHarmGold standard (test)MedicineStandard of careRisk analysis (engineering)Health technologyEvidence-based medicineIntensive care medicineOperations managementAlternative medicineHealth careEngineeringPsychologySurgeryEconomics

Abstract

fetched live from OpenAlex

New orthopaedic technology is constantly being developed to help improve patient care. New technology may lead to a waste of resources or lead to harm for the patient if it is not properly evaluated before it is accepted as a standard of care. The purpose of this article is to assess how new technology can be implemented safely while maintaining an environment that allows for surgical innovation through an evidence-based approach. Although randomized controlled trials (Level-I evidence) are typically seen as the so-called gold standard with regard to treatment efficacy, randomized trials may not be the most effective form of evaluating a new technology. In many circumstances, a prospective cohort series or large registry that documents outcomes and adverse events may be more effective and practical for the evaluation of a new surgical technology.

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)0.004
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.861
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.228
GPT teacher head0.397
Teacher spread0.169 · 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 designOther design
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

Citations19
Published2009
Admission routes1
Has abstractyes

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