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Record W2057353650 · doi:10.1016/j.ahj.2015.04.022

Design and methods of the Echo WISELY (Will Inappropriate Scenarios for Echocardiography Lessen SignificantlY) study: An investigator-blinded randomized controlled trial of education and feedback intervention to reduce inappropriate echocardiograms

2015· article· en· W2057353650 on OpenAlexafffund
R. Sacha Bhatia, Noah Ivers, Cindy X Yin, Dorothy Myers, Gillian C. Nesbitt, Jeremy Edwards, Kibar Yared, Rishi K. Wadhera, Justina Wu, Brian M. Wong, Adina Weinerman, Steven Shadowitz, Amer M. Johri, Michael E. Farkouh, Paaladinesh Thavendiranathan, Jacob A. Udell, Sherryn Rambihar, Chi-Ming Chow, Judith G. Hall, Kevin E. Thorpe, Harry Rakowski, Rory B. Weiner

Bibliographic record

VenueAmerican Heart Journal · 2015
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsUniversity of TorontoUniversity Health NetworkThe Scarborough HospitalSunnybrook HospitalMount Sinai HospitalSt. Michael's HospitalQueen's UniversityWomen's College Hospital
FundersUniversity Health NetworkAmerican College of Cardiology Foundation
KeywordsMedicineRandomized controlled trialIntervention (counseling)AmbulatoryFamily medicineEmergency medicineNursingSurgery

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.013
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.081
GPT teacher head0.420
Teacher spread0.339 · 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 designRandomized trial
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

Citations18
Published2015
Admission routes2
Has abstractno

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