{"id":"W3135588948","doi":"10.1109/jproc.2021.3058954","title":"Toward Causal Representation Learning","year":2021,"lang":"en","type":"article","venue":"Proceedings of the IEEE","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":1024,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; Université de Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Representation (politics); Computer science; Artificial intelligence; Cognitive psychology; Psychology; Cognitive science; Political science","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":[0.01497126,0.001354846,0.001686558,0.004992966,0.001613571,0.004935701,0.002584985,0.002791031,0.008264271],"category_scores_gemma":[0.05877562,0.001040288,0.002267412,0.004106398,0.005700162,0.008183528,0.006202444,0.007975301,0.001768802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002756962,"about_ca_system_score_gemma":0.00404861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003451873,"about_ca_topic_score_gemma":0.003448799,"domain_scores_codex":[0.9898922,0.006850328,0.0003020223,0.001317364,0.001371813,0.0002663101],"domain_scores_gemma":[0.9601266,0.03170044,0.001616187,0.003708826,0.002251732,0.0005962354],"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":[0.00001777964,0.00002671217,0.0004701388,0.0001149449,0.000057561,0.00004420727,0.0002208086,0.01057346,0.00009847691,0.9542955,0.003250247,0.03083014],"study_design_scores_gemma":[0.00000760203,0.000005532725,0.00005910197,0.0000463162,0.000008845393,0.00002052419,0.00003035423,0.03011246,0.0000634371,0.9649795,0.004659194,0.000007178305],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001300965,0.001093403,0.9872207,0.004571913,0.0001263789,0.00004654537,0.0001986043,0.0001458355,0.005295632],"genre_scores_gemma":[0.1718221,0.005137048,0.8089446,0.003321216,0.001617044,0.000695714,0.001320682,0.0002221073,0.006919493],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01497126,"threshold_uncertainty_score":0.07917655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04589998154648502,"score_gpt":0.2709303443717051,"score_spread":0.2250303628252201,"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."}}