{"id":"W4402581782","doi":"10.1038/s41592-024-02405-4","title":"Propensity score matching","year":2024,"lang":"en","type":"article","venue":"Nature Methods","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Propensity score matching; Matching (statistics); Computational biology; Computer science; Biology; Medicine; Internal medicine; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008826026,0.0007481175,0.001780518,0.002450952,0.00107023,0.002495946,0.002247307,0.002292723,0.05377578],"category_scores_gemma":[0.0390126,0.0006405245,0.002081167,0.003337873,0.0009312441,0.002148957,0.002354349,0.002218471,0.01319349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007731226,"about_ca_system_score_gemma":0.00343189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001560618,"about_ca_topic_score_gemma":0.00164037,"domain_scores_codex":[0.9915105,0.005016983,0.0003668618,0.001531959,0.00111072,0.0004630435],"domain_scores_gemma":[0.990699,0.003751014,0.0007521075,0.003745884,0.0007905804,0.0002614209],"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":[0.0004212067,0.000331292,0.007423037,0.0002705972,0.000515999,0.0001855981,0.0001071634,0.01168377,0.0005796207,0.6331713,0.04939993,0.2959105],"study_design_scores_gemma":[0.0004173809,0.0001861869,0.002856887,0.0001238164,0.0003019764,0.0005977154,0.00006227589,0.09480957,0.001043834,0.8449764,0.05458094,0.00004301044],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006661286,0.0004483355,0.9701607,0.001485444,0.0003873458,0.0006687529,0.002013374,0.0007455598,0.01742912],"genre_scores_gemma":[0.3958421,0.001348904,0.4992314,0.002851591,0.001299226,0.003122104,0.006657992,0.0005582033,0.08908846],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05377578,"threshold_uncertainty_score":0.1798979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2954066621601936,"score_gpt":0.548128130712416,"score_spread":0.2527214685522223,"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."}}