{"id":"W3104195492","doi":"","title":"Relational autoencoder for feature extraction","year":2017,"lang":"en","type":"article","venue":"UTS ePRESS (University of Technology Sydney)","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":198,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Autoencoder; Computer science; Feature extraction; Artificial intelligence; Pattern recognition (psychology); Feature (linguistics); Data mining; Artificial neural network","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":[0.0007004554,0.0006812792,0.0005504736,0.000434197,0.0001798242,0.0007004261,0.0006677146,0.0007761306,0.003757093],"category_scores_gemma":[0.001668438,0.000349622,0.0006825601,0.0007323145,0.0005069234,0.0009723564,0.0007827313,0.001618195,0.001881891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006175231,"about_ca_system_score_gemma":0.0004905949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002797079,"about_ca_topic_score_gemma":0.002807493,"domain_scores_codex":[0.9995393,0.00009066982,0.00003068261,0.0001434729,0.0001668984,0.00002900951],"domain_scores_gemma":[0.9995986,0.0001639833,0.00004406859,0.0001125685,0.00006783957,0.00001301585],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000135933,0.00006370636,0.000892619,0.0001464748,0.0001353907,0.0001686756,0.00007061019,0.3027722,0.01803354,0.04354249,0.007413407,0.626625],"study_design_scores_gemma":[0.000003095873,0.00002696055,0.0002686606,0.00001689148,0.00001689309,0.00007421683,0.000005808506,0.9796484,0.004177142,0.009805609,0.00594772,0.00000852743],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004335464,0.0009754351,0.991838,0.0001554931,0.00006583917,0.00002190512,0.0001124423,0.0004417728,0.002053526],"genre_scores_gemma":[0.472313,0.003534221,0.4990495,0.000446234,0.0002065235,0.0001622834,0.001773612,0.000226369,0.0222883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003757093,"threshold_uncertainty_score":0.01256871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02418145173831861,"score_gpt":0.237948323936502,"score_spread":0.2137668721981834,"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."}}