MétaCan
Menu
Back to cohort
Record W4280546958 · doi:10.1038/s41433-022-02108-0

Sensitivity analysis in clinical trials: three criteria for a valid sensitivity analysis

2022· letter· en· W4280546958 on OpenAlexaff
Sameer Parpia, Tim P. Morris, Mark Phillips, Charles C. Wykoff, David Steel, Lehana Thabane, Mohit Bhandari, Varun Chaudhary, Sobha Sivaprasad, Peter K. Kaiser, David Sarraf, Sophie J. Bakri, Sunir J. Garg, Rishi P. Singh, Frank G. Holz, Tien Yin Wong, Robyn H. Guymer

Bibliographic record

VenueEye · 2022
Typeletter
Languageen
FieldMathematics
TopicStatistical Methods in Clinical Trials
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcMaster UniversityImpact
FundersMedical Research CouncilNational Institute for Health and Care Research
KeywordsSensitivity (control systems)MedicineEngineering

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)0.568
metaresearch head score (Gemma)0.851
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.432
Threshold uncertainty score0.533

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5680.851
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0110.016
Bibliometrics0.0070.004
Science and technology studies0.0050.016
Scholarly communication0.0120.012
Open science0.0080.010
Research integrity0.0370.034
Insufficient payload (model declined to judge)0.0050.001

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 head0.756
GPT teacher head0.653
Teacher spread0.102 · 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 designTheoretical or conceptual
DomainMethods
GenreCommentary

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

Citations33
Published2022
Admission routes1
Has abstractno

Explore more

Same venueEyeSame topicStatistical Methods in Clinical TrialsFrench-language works237,207