{"id":"W4382318232","doi":"10.1609/aaai.v37i9.26266","title":"Disentangled Representation for Causal Mediation Analysis","year":2023,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Australian Research Council; Natural Sciences and Engineering Research Council of Canada; University of South Australia","keywords":"Confounding; Mediation; Latent variable; Causal inference; Observational study; Econometrics; Causality (physics); Representation (politics); Computer science; Outcome (game theory); Structural equation modeling; Affect (linguistics); Mechanism (biology); Causal model; Artificial intelligence; Machine learning; Psychology; Statistics; Mathematics","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":[0.004322407,0.001044823,0.001307642,0.001032959,0.0003890813,0.001007832,0.001866212,0.00132969,0.003927343],"category_scores_gemma":[0.01514234,0.0005880399,0.001956396,0.001125586,0.0009091161,0.001840492,0.001921854,0.003172577,0.0003866085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009186775,"about_ca_system_score_gemma":0.001780975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005790565,"about_ca_topic_score_gemma":0.00717713,"domain_scores_codex":[0.9976411,0.001449554,0.0001077472,0.0004203828,0.0002332528,0.0001480395],"domain_scores_gemma":[0.9943424,0.00463092,0.000236001,0.0004634078,0.0002443583,0.0000829088],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004074514,0.0002609737,0.008702382,0.0007337306,0.001253634,0.0003202732,0.0005559577,0.4277281,0.003201574,0.139953,0.007508551,0.4093743],"study_design_scores_gemma":[0.00003654181,0.00004433263,0.0009280935,0.00006872249,0.0001236495,0.00005232521,0.00003473203,0.87977,0.0007287489,0.1156548,0.002537858,0.0000201864],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007287476,0.001103035,0.9897028,0.0005169216,0.00005577541,0.00004788276,0.0002910227,0.0003200343,0.0006750462],"genre_scores_gemma":[0.5799923,0.00263854,0.4083371,0.001176501,0.0003062981,0.0007413793,0.002147375,0.0002441514,0.004416507],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005790565,"threshold_uncertainty_score":0.02285933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3166754638276828,"score_gpt":0.4577078551709374,"score_spread":0.1410323913432546,"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."}}