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Record W3005922843 · doi:10.1016/j.cjca.2020.01.028

Identification and Evaluation of Controlled Trials in Pediatric Cardiology: Crowdsourced Scoping Review and Creation of Accessible Searchable Database

2020· article· en· W3005922843 on OpenAlexaffvenue
Jenna Ashkanase, Nassr Nama, Ryan Sandarage, Joshua Penslar, Ronish Gupta, Sophia Ly, Melissa Wan, Phillip Tsang, Alex Nantsios, Erik Jacques, Hsin Yun Yang, Hajra Mazhar, Gang Xu, Maria Lorena Rodriguez, Samantha Gerber, Laurie M. Laird, Margaret Sampson, Derek T. H. Wong, James Dayre McNally

Bibliographic record

VenueCanadian Journal of Cardiology · 2020
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsCarleton UniversityWestern UniversityMcMaster UniversityUniversity of TorontoSickKids FoundationChildren's Hospital of Eastern OntarioUniversity of British ColumbiaHospital for Sick ChildrenUniversity of Ottawa
Fundersnot available
KeywordsMedicineRandomized controlled trialInterquartile rangeMEDLINEDatabaseClinical trialPsychological interventionRandomizationOnline databaseData extractionPediatricsInternal medicine

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 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)0.283
metaresearch head score (Gemma)0.630
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.717
Threshold uncertainty score0.884

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2830.630
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0220.017
Bibliometrics0.0490.031
Science and technology studies0.0030.003
Scholarly communication0.0140.010
Open science0.0090.014
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0210.002

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 head0.120
GPT teacher head0.403
Teacher spread0.284 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designSystematic review
DomainMethods
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

Citations15
Published2020
Admission routes2
Has abstractno

Explore more

Same venueCanadian Journal of Cardiology→Same topicCongenital Heart Disease Studies→French-language works237,207→