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Record W2996968603 · doi:10.1177/0009922819896098

Development and Utility of Quality Metrics for Ambulatory Pediatric Cardiology in Kawasaki Disease

2020· article· en· W2996968603 on OpenAlex
David F. Teitel, Jane W. Newburger, Nicole Sutton, Lloyd Y. Tani, Ashraf S. Harahsheh, Pei-Ni Jone, Deborah Mensch, Timothy B. Cotts, Alex Davidson, Nagib Dahdah, Walter H. Johnson, Michael A. Portman

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

VenueClinical Pediatrics · 2020
Typearticle
Languageen
FieldMedicine
TopicKawasaki Disease and Coronary Complications
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineKawasaki diseaseAmbulatoryCardiologyIntensive care medicineQuality (philosophy)Internal medicineDisease

Abstract

fetched live from OpenAlex

The Adult Congenital and Pediatric Cardiology (ACPC) Section of the American College of Cardiology sought to develop quality indicators/metrics for ambulatory pediatric cardiology practice. The objective of this study was to report the creation of metrics for patients with Kawasaki disease. Over a period of 5 months, 12 pediatric cardiologists developed 24 quality metrics based on the most relevant statements, guidelines, and research studies pertaining to Kawasaki disease. Of the 24 metrics, the 8 metrics deemed the most important, feasible, and valid were sent on to the ACPC for consideration. Seven of the 8 metrics were approved using the RAND method by an expert panel. All 7 metrics approved by the ACPC council were accepted by ACPC membership after an "open comments" process. They have been disseminated to the pediatric cardiology community for implementation by the ACPC Quality Network.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.005
Threshold uncertainty score0.565

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.434
Teacher spread0.206 · 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