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Record W4318617696 · doi:10.2139/ssrn.4326210

A Methodological Review Found that Randomization is Often Fragile in Stepped-Wedge Cluster Randomized Trials

2023· review· en· W4318617696 on OpenAlexaff
Monica Taljaard, Pascale Nevins, Kendra Davis‐Plourde, Jules Pereira Macedo, Yongdong Ouyang, Mary Ryan, Guangyu Tong, Xueqi Wang, Can Meng, Luis Ortiz‐Reyes, Fan Li, Agnès Caille

Bibliographic record

VenueSSRN Electronic Journal · 2023
Typereview
Languageen
FieldMathematics
TopicStatistical Methods and Inference
Canadian institutionsWestern UniversityOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsCRTSRandomizationCovariateRestricted randomizationRandomized controlled trialCluster randomised controlled trialCluster (spacecraft)MedicineStatisticsComputer scienceMathematicsSurgery

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptMetaresearch
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.216
metaresearch head score (Gemma)0.610
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.784
Threshold uncertainty score0.967

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2160.610
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0080.008
Bibliometrics0.0030.005
Science and technology studies0.0010.004
Scholarly communication0.0050.005
Open science0.0030.004
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0120.001

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 head0.607
GPT teacher head0.551
Teacher spread0.056 · 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

Labeled directly by 2 models reading the full record.

Study designSystematic review
DomainMethods
GenreReview

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
Published2023
Admission routes1
Has abstractno

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