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Record W4205276167 · doi:10.1016/j.ahj.2021.11.013

Corrigendum to ‘Rationale and design of the comparison of outcomes and access to care for heart failure (COACH) trial: a stepped wedge cluster randomized trial’ American Heart Journal 2021; 240:1-10

2022· erratum· en· W4205276167 on OpenAlexaff
Douglas S. Lee, Sharon E. Straus, Peter C. Austin, Shanas Mohamed, Monica Taljaard, Alice Chong, Jiming Fang, Treesa Prasad, Michael E. Farkouh, Michael J. Schull, Susanna Mak, Heather J. Ross

Bibliographic record

VenueAmerican Heart Journal · 2022
Typeerratum
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsHealth Sciences CentreSinai Health SystemSunnybrook Health Science CentreOttawa HospitalUniversity of OttawaUniversity Health NetworkUniversity of TorontoInstitute for Clinical Evaluative SciencesTed Rogers Centre for Heart Research
Fundersnot available
KeywordsMedicineHeart failureRandomized controlled trialCluster randomised controlled trialCluster (spacecraft)Wedge (geometry)Physical therapyInternal medicineCardiology

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)0.042
metaresearch head score (Gemma)0.282
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.069
Threshold uncertainty score0.231

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.282
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0030.003
Science and technology studies0.0030.003
Scholarly communication0.0040.001
Open science0.0050.002
Research integrity0.0120.020
Insufficient payload (model declined to judge)0.0690.039

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 head0.332
GPT teacher head0.461
Teacher spread0.129 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2022
Admission routes1
Has abstractno

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