MétaCan
Menu
← Back to cohort
Record W1492448000 · doi:10.1002/9780470691922.ch1

Randomized Controlled Trials: The Basics

2007· other· en· W1492448000 on OpenAlexaff
Alejandro R. Jadad, Murray W. Enkin

Bibliographic record

Venuenot available
Typeother
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsMcMaster UniversityUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsRandomized controlled trialRandomizationN of 1 trialMedicinePsychological interventionComputer scienceNursingSurgery

Abstract

fetched live from OpenAlex

This chapter contains section titled: What is a randomized controlled trial ? What does random allocation mean ? What is the purpose of random allocation ? How can randomization be achieved ? What can be randomized in RCTs ? When are randomized trials needed ? How are RCTs used ? How are trials managed and overseen ? Can RCTs answer all questions related to health care interventions ? Our musings References

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.

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)0.263
metaresearch head score (Gemma)0.458
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.737
Threshold uncertainty score0.909

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2630.458
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0170.006
Bibliometrics0.0130.018
Science and technology studies0.0020.016
Scholarly communication0.0160.018
Open science0.0080.006
Research integrity0.0190.026
Insufficient payload (model declined to judge)0.0360.031

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 head0.829
GPT teacher head0.586
Teacher spread0.243 · 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 designNot applicable
DomainMethods
GenreMethods

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

Citations4
Published2007
Admission routes1
Has abstractyes

Explore more

Same topicMeta-analysis and systematic reviews→French-language works237,207→