{"id":"W4408502051","doi":"10.1038/s41592-025-02629-y","title":"Propensity score weighting","year":2025,"lang":"en","type":"article","venue":"Nature Methods","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Propensity score matching; Weighting; Computational biology; Computer science; Biology; Internal medicine; Medicine","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":[0.008891935,0.0009511694,0.001624945,0.002643432,0.0009577711,0.002761878,0.001923123,0.002019296,0.04421834],"category_scores_gemma":[0.04107661,0.0006360479,0.001880656,0.003320718,0.0008951694,0.002206678,0.002127002,0.002495965,0.01087799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007183289,"about_ca_system_score_gemma":0.002658064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001681897,"about_ca_topic_score_gemma":0.002106633,"domain_scores_codex":[0.9918422,0.005064189,0.0003203159,0.001297186,0.001159556,0.0003165889],"domain_scores_gemma":[0.9907495,0.004180815,0.0005731593,0.003201842,0.00105362,0.0002409916],"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":[0.0001723788,0.0002116152,0.003196309,0.0002337011,0.0004247423,0.00009404284,0.00009739688,0.01284505,0.0006162974,0.6380492,0.03732197,0.3067373],"study_design_scores_gemma":[0.000209397,0.000131224,0.001994201,0.0001491303,0.0002697546,0.0003706513,0.00005279038,0.1045128,0.00108866,0.8305981,0.06057638,0.00004706059],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002268945,0.0002663888,0.9854304,0.0005372823,0.0002349934,0.0003232007,0.0006296533,0.0004562675,0.009852873],"genre_scores_gemma":[0.2296907,0.001247086,0.690015,0.001595462,0.0009857276,0.00229733,0.003529431,0.0006745622,0.06996465],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04421834,"threshold_uncertainty_score":0.1479251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2518400596419759,"score_gpt":0.5445541503713819,"score_spread":0.292714090729406,"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."}}