{"id":"W4293118255","doi":"10.1007/978-3-031-01588-5_9","title":"Deep Generative Models","year":2020,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on artificial intelligence and machine learning","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Generative grammar; Computer science; Graph; Theoretical computer science; Key (lock); Artificial intelligence; Generative model; Process (computing); Data science; Programming language","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006732211,0.0004171953,0.0005651963,0.0003599295,0.0005333137,0.0004006347,0.0005161882,0.0003118716,0.002759636],"category_scores_gemma":[0.00175119,0.0003222517,0.0002349528,0.0001537571,0.0001731482,0.0001125902,0.0001486241,0.0009062474,0.0008842637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003551791,"about_ca_system_score_gemma":0.00004280495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002830504,"about_ca_topic_score_gemma":0.00008054517,"domain_scores_codex":[0.9970149,0.0001322309,0.0008198236,0.0009613443,0.0008495649,0.0002221848],"domain_scores_gemma":[0.9963236,0.002436743,0.0004249834,0.0004353375,0.000206738,0.0001725387],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003172749,0.000008709254,0.000001563062,0.000002572102,0.00002033302,0.000003720348,0.0002502476,0.06161277,0.00007875471,0.4616168,0.0002102273,0.4761626],"study_design_scores_gemma":[0.000005255027,0.00007886712,0.000001127046,0.00002935609,0.0000267952,0.00000216518,0.0000531841,0.2885998,0.005258023,0.6468727,0.05880859,0.0002641486],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00002277327,0.0005552812,0.6612747,0.003695901,0.00008572343,0.0004033062,0.00002718888,0.0002159276,0.3337193],"genre_scores_gemma":[0.9392917,0.0005969138,0.003716227,0.002068445,0.0005524944,0.00007250356,0.00003232217,0.0001118548,0.05355757],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9392689,"threshold_uncertainty_score":0.9999229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2066218497401466,"score_gpt":0.3742896252103348,"score_spread":0.1676677754701882,"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."}}