{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001680371,0.0001613366,0.0002407089,0.00009816678,0.00005689664,0.0000783904,0.0002016682,0.0003434989,0.0001013644],"category_scores_gemma":[0.001735277,0.0001190426,0.00008284872,0.0002955267,0.00004041581,0.0002045946,0.0001173491,0.001388877,0.00001685909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007218286,"about_ca_system_score_gemma":0.0000429578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003652233,"about_ca_topic_score_gemma":0.000003467922,"domain_scores_codex":[0.998876,0.0002566365,0.0001849674,0.0002940587,0.0001818826,0.000206404],"domain_scores_gemma":[0.9979895,0.001484931,0.00003900073,0.0003651824,0.00007014396,0.00005122748],"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":[0.000006716359,0.00001876835,0.00004036483,0.0002960433,0.00002983952,0.00005751203,0.0003311953,5.605e-7,0.03341727,0.7801753,0.004924588,0.1807019],"study_design_scores_gemma":[0.00002278113,0.00001906718,0.0001052109,0.0001977933,0.00002373067,0.00003446138,0.00001324494,0.00009863821,0.08496746,0.8977368,0.01663659,0.0001442454],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01648153,0.001511298,0.966413,0.0003302529,0.0005655805,0.0002805046,0.000003856696,0.001711269,0.0127027],"genre_scores_gemma":[0.08435088,0.00001838225,0.9141338,0.0002148441,0.0001605924,0.00002251254,0.00000202795,0.00004205725,0.001054921],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1805576,"threshold_uncertainty_score":0.6034057,"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."}}