{"id":"W3091221243","doi":"","title":"Semi-supervised Sequential Generative Models","year":2020,"lang":"en","type":"article","venue":"Uncertainty in Artificial Intelligence","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"MNIST database; Computer science; Estimator; Latent variable; Generative model; Generative grammar; Machine learning; Artificial intelligence; Trajectory; Forcing (mathematics); Variance (accounting); Variable (mathematics); Deep learning; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001262979,0.0009828527,0.00105762,0.0005774359,0.0003219871,0.0008079034,0.002082197,0.001140947,0.003535292],"category_scores_gemma":[0.004312427,0.0007109244,0.0009965568,0.000573729,0.001359139,0.001395427,0.001539143,0.002001533,0.0007949909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007822459,"about_ca_system_score_gemma":0.0007889125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002529284,"about_ca_topic_score_gemma":0.006007788,"domain_scores_codex":[0.9993423,0.0002387869,0.00002695691,0.0002155261,0.0001141086,0.00006238152],"domain_scores_gemma":[0.9976588,0.001420633,0.0002708221,0.0003600513,0.0001864951,0.0001031828],"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":[0.00009259264,0.0000482416,0.001104864,0.00008037311,0.000066206,0.0001046768,0.0001179221,0.9064991,0.002556028,0.04182544,0.002347028,0.0451575],"study_design_scores_gemma":[0.000003518337,0.000008768184,0.00007260042,0.000004118031,0.000003666134,0.00001602863,0.000003243309,0.9889755,0.0003312003,0.01021741,0.0003601503,0.000003806922],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009587938,0.0001328053,0.9885352,0.0001745007,0.00002515386,0.00002695382,0.0001622948,0.0004157251,0.0009394343],"genre_scores_gemma":[0.7548983,0.0003306209,0.2322157,0.0003413368,0.0001610746,0.000302959,0.001268878,0.0003505554,0.01013064],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003535292,"threshold_uncertainty_score":0.01182675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09722466294154446,"score_gpt":0.2841124223971038,"score_spread":0.1868877594555593,"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."}}