{"id":"W4385698578","doi":"10.1186/s12874-023-01995-5","title":"Genetic matching for time-dependent treatments: a longitudinal extension and simulation study","year":2023,"lang":"en","type":"article","venue":"BMC Medical Research Methodology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Canadian Centre for Applied Research in Cancer Control","funders":"Terry Fox Research Institute; Health Innovation Network South London; Genome British Columbia; Genome Canada","keywords":"Covariate; Propensity score matching; Matching (statistics); Statistics; Confounding; Baseline (sea); Computer science; Mathematics; Econometrics; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04560228,0.0007884958,0.0009579841,0.001291814,0.0008304054,0.00108018,0.002052415,0.001648497,0.002983259],"category_scores_gemma":[0.09286261,0.0005135603,0.002508735,0.001632114,0.001231641,0.001416996,0.001593719,0.002679208,0.0002540924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002395208,"about_ca_system_score_gemma":0.002584572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01809083,"about_ca_topic_score_gemma":0.01244287,"domain_scores_codex":[0.9869665,0.01115041,0.0002782222,0.0008804448,0.000394124,0.0003302691],"domain_scores_gemma":[0.8495591,0.1315799,0.006373938,0.007456908,0.003724254,0.001305872],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001967973,0.001618443,0.08458783,0.0002676566,0.001311071,0.0006203087,0.0004580524,0.8527909,0.000464046,0.02238395,0.003197459,0.03033229],"study_design_scores_gemma":[0.0006591962,0.0006232425,0.005914854,0.00008432747,0.0002645032,0.0001388258,0.000104887,0.9788422,0.0003278055,0.01196449,0.001034322,0.00004139242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8072731,0.001123741,0.1845871,0.001869218,0.00009740579,0.0009458512,0.001160992,0.0002349355,0.002707678],"genre_scores_gemma":[0.9219372,0.0004642215,0.07435466,0.0004106204,0.00006865893,0.000945534,0.001086719,0.0000389737,0.0006933314],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.04560228,"threshold_uncertainty_score":0.2411708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3928024778635604,"score_gpt":0.5465209185638702,"score_spread":0.1537184407003098,"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."}}