{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001134401,0.0009500336,0.0009392505,0.0005377426,0.0003934636,0.000945579,0.001752673,0.001470837,0.004455565],"category_scores_gemma":[0.004238734,0.0006512604,0.0007739821,0.0006103136,0.001300706,0.001680855,0.001396105,0.002645344,0.000816384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001118016,"about_ca_system_score_gemma":0.0008774378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006566517,"about_ca_topic_score_gemma":0.009060045,"domain_scores_codex":[0.99962,0.0001088036,0.00001653345,0.0001294506,0.00007416899,0.0000511276],"domain_scores_gemma":[0.9985814,0.0008824546,0.0001093235,0.0002059152,0.0001510174,0.00006993334],"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":[0.00008010297,0.00002989649,0.0009544617,0.00004290486,0.00003812531,0.00004755335,0.00004033553,0.9245374,0.001374702,0.03735569,0.003254163,0.03224469],"study_design_scores_gemma":[0.000003183066,0.000005271484,0.0000385422,0.000003551197,0.000001575968,0.000004516169,0.000001922822,0.9932477,0.0002762275,0.006181028,0.0002340602,0.000002321127],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0352289,0.0006392461,0.9578032,0.0006642399,0.0001006651,0.00004805382,0.0004110406,0.0008757271,0.004228879],"genre_scores_gemma":[0.7924495,0.0005476443,0.1913723,0.0004035753,0.0001112483,0.0002034822,0.001193479,0.0003726008,0.01334603],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006566517,"threshold_uncertainty_score":0.01490533,"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."}}