{"id":"W3132648081","doi":"10.48550/arxiv.2102.09532","title":"Clockwork Variational Autoencoders","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Clockwork; Computer science; Benchmark (surveying); Artificial intelligence; Abstraction; Hierarchy; Machine learning; Term (time); Pattern recognition (psychology)","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"],"consensus_categories":[],"category_scores_codex":[0.000231213,0.0003092539,0.0003307405,0.00014185,0.0002311165,0.0003473669,0.001514443,0.0002800807,0.0001605956],"category_scores_gemma":[0.00005784645,0.0003668741,0.0002935937,0.0006236689,0.00007639839,0.0005047504,0.002035877,0.0005007195,0.00006012383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001794412,"about_ca_system_score_gemma":0.0004730205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000128675,"about_ca_topic_score_gemma":0.00004488261,"domain_scores_codex":[0.9978477,0.0002612092,0.0001974091,0.001210512,0.0001273196,0.0003558365],"domain_scores_gemma":[0.9981084,0.0001411405,0.000210029,0.001112095,0.0002638734,0.0001644865],"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":[0.000005214628,0.00005595106,0.00032121,0.00001311829,0.0001210261,0.0002046355,0.0001705858,0.9326751,0.00001558348,0.06478804,0.00109573,0.0005337694],"study_design_scores_gemma":[0.0002100587,0.00001550574,0.001143998,0.0000524254,0.00004969761,0.000003179762,0.00006341653,0.9791692,0.00008012143,0.01784706,0.0009665841,0.0003986951],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004259631,0.0001163433,0.9896845,0.000348146,0.001560553,0.0001507694,0.000008367131,0.0001821693,0.003689564],"genre_scores_gemma":[0.9433576,0.0001255109,0.05449543,0.0002552211,0.0002598991,0.000001015452,0.00003236594,0.00001498995,0.001458008],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9390979,"threshold_uncertainty_score":0.9998783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05467910025840562,"score_gpt":0.1715634824985009,"score_spread":0.1168843822400953,"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."}}