{"id":"W2922251441","doi":"10.1007/s00500-019-03916-5","title":"Granular autoencoders: concepts and design","year":2019,"lang":"en","type":"article","venue":"Soft Computing","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"King Abdulaziz University","keywords":"Granularity; Autoencoder; Computer science; Cluster analysis; Artificial intelligence; Representation (politics); Key (lock); Granular computing; Machine learning; Artificial neural network; Data mining; Rough set","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":[0.001684717,0.0004673349,0.0008186919,0.0005666888,0.0002304498,0.001660378,0.0008665696,0.00107258,0.001836394],"category_scores_gemma":[0.004682987,0.000590137,0.0005003702,0.0008597485,0.0008449164,0.001795231,0.0009872152,0.001430857,0.0004165973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004671646,"about_ca_system_score_gemma":0.0007014357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001290693,"about_ca_topic_score_gemma":0.001329627,"domain_scores_codex":[0.9995622,0.0001202651,0.00004699952,0.0001075673,0.0001290618,0.0000339056],"domain_scores_gemma":[0.9983695,0.0009914681,0.0001139782,0.0002322151,0.0002389251,0.00005381886],"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":[0.0001394671,0.0001083735,0.00135501,0.0003823049,0.0001312567,0.0001019439,0.0001241905,0.3002084,0.006887796,0.2630669,0.003506664,0.4239877],"study_design_scores_gemma":[0.00001201169,0.00004888925,0.0002793754,0.00004911998,0.0000311616,0.00005283497,0.00001763318,0.9331306,0.001895053,0.06181522,0.002655924,0.00001221025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004004064,0.0007663572,0.9938529,0.0001811815,0.00006084878,0.00002412442,0.00003457622,0.0002049043,0.0008710756],"genre_scores_gemma":[0.3381855,0.003069188,0.6529039,0.0002663751,0.0002782961,0.000296835,0.0001931623,0.0001126177,0.004694038],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001836394,"threshold_uncertainty_score":0.008909702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01652275673031815,"score_gpt":0.2399982391741039,"score_spread":0.2234754824437858,"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."}}