{"id":"W3125376726","doi":"10.48550/arxiv.2106.13024","title":"Symmetric Wasserstein Autoencoders","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Computer science; Artificial intelligence; Mathematics","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":[0.00152513,0.001226361,0.001133202,0.0006533076,0.0003164194,0.001087986,0.001615245,0.001383885,0.003130567],"category_scores_gemma":[0.004717162,0.0007157616,0.001087174,0.0006351598,0.001666355,0.001788161,0.001600954,0.002448477,0.00091982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001068227,"about_ca_system_score_gemma":0.0009045204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00229582,"about_ca_topic_score_gemma":0.002903075,"domain_scores_codex":[0.9992639,0.0002752898,0.00003659408,0.0001883134,0.0001695023,0.0000664125],"domain_scores_gemma":[0.9984558,0.0009771162,0.0001317112,0.0002317062,0.0001483166,0.00005535951],"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":[0.00005274555,0.00003438866,0.0004787408,0.00007636534,0.00005949874,0.00007598293,0.00005434058,0.8121347,0.003140448,0.1320064,0.001695469,0.05019096],"study_design_scores_gemma":[0.000003584205,0.00001010516,0.00004379212,0.000008230736,0.000005050337,0.00001879359,0.000002773544,0.9711326,0.0006257987,0.02752676,0.000617398,0.000005018572],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004330975,0.0002061385,0.9932614,0.0001359384,0.00002885729,0.00001729658,0.00006750643,0.0002125981,0.001739275],"genre_scores_gemma":[0.5716452,0.001169113,0.4068152,0.0005333707,0.0001686278,0.0002703281,0.0007659614,0.0004640327,0.0181682],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003130567,"threshold_uncertainty_score":0.01047277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06214300876735093,"score_gpt":0.1739100751952475,"score_spread":0.1117670664278965,"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."}}