{"id":"W4399600420","doi":"10.1093/jrsssc/qlae028","title":"Two-phase biomarker studies for disease progression with multiple registries","year":2024,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series C (Applied Statistics)","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sampling design; Sampling (signal processing); Inverse probability; Inverse probability weighting; Covariate; Pooling; Missing data; Stratified sampling; Statistics; Weighting; Simple random sample; Computer science; Mathematics; Bayesian probability; Artificial intelligence; Medicine; Posterior probability; Population","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002637791,0.0005229118,0.001244127,0.00004438005,0.0005237976,0.0003004338,0.0005639418,0.0001487621,0.0001387739],"category_scores_gemma":[0.03917734,0.0002876325,0.0004429584,0.0003330114,0.00186434,0.0001243903,0.0002357612,0.0007373751,0.000006251772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002565845,"about_ca_system_score_gemma":0.0004750164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002689668,"about_ca_topic_score_gemma":0.000007276572,"domain_scores_codex":[0.9953166,0.0004313972,0.001844929,0.000535594,0.001227464,0.000644017],"domain_scores_gemma":[0.9379791,0.05950734,0.00084274,0.000484809,0.0007126018,0.0004734198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.006433627,0.0005500543,0.00006307243,0.002370711,0.001734477,0.0001517445,0.0005367922,0.00006023783,0.0001291167,0.7367904,0.2047108,0.04646897],"study_design_scores_gemma":[0.004335829,0.001029223,0.0002383788,0.0008474158,0.001822353,0.00002751308,0.0008825041,0.0110644,0.0002252938,0.9668669,0.01218742,0.0004727371],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00077156,0.0007223198,0.9872036,0.001672142,0.001507261,0.001259497,0.006620772,0.00009771313,0.0001451377],"genre_scores_gemma":[0.04992408,0.0001066105,0.9482166,0.0001885555,0.0006433174,0.0001519661,0.00001742215,0.0001174244,0.0006340131],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2300765,"threshold_uncertainty_score":0.9999576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2747011443187014,"score_gpt":0.5343761593589086,"score_spread":0.2596750150402072,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}