{"id":"W3181507617","doi":"","title":"Learning Input and Recurrent Weight Matrices in Echo State Networks","year":2016,"lang":"en","type":"article","venue":"","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Recurrent neural network; Computer science; Activation function; Recursion (computer science); Echo state network; Backpropagation; Matrix (chemical analysis); Echo (communications protocol); Artificial intelligence; Algorithm; Function (biology); 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":[0.001045419,0.0006451833,0.0004158389,0.0003505332,0.0002882819,0.0009035919,0.0008751912,0.0007640827,0.00185734],"category_scores_gemma":[0.004775272,0.0004879455,0.000426546,0.0004041329,0.0006697372,0.002170195,0.0009158014,0.00134603,0.0005552893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004425373,"about_ca_system_score_gemma":0.0005489604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002650887,"about_ca_topic_score_gemma":0.004453307,"domain_scores_codex":[0.9996393,0.0001065106,0.00002494492,0.0001119096,0.00008051684,0.00003684227],"domain_scores_gemma":[0.9990537,0.0004745945,0.0001149466,0.0001021363,0.0002158822,0.00003878018],"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":[0.0001330482,0.0001076348,0.002224207,0.000132103,0.0001041254,0.0001662432,0.0002648878,0.6416732,0.01431558,0.05398254,0.002083853,0.2848126],"study_design_scores_gemma":[0.000003722722,0.00002209911,0.00020563,0.000007348935,0.000008158201,0.00002176048,0.00001223702,0.9869559,0.002388174,0.009768127,0.000599204,0.000007642514],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02067384,0.000159473,0.9771792,0.0001020699,0.00004056292,0.00001966192,0.0000438865,0.0004007578,0.001380474],"genre_scores_gemma":[0.7024145,0.0004667759,0.2898155,0.0001854902,0.00006410639,0.0001111323,0.0002994489,0.0001543449,0.006488616],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002650887,"threshold_uncertainty_score":0.006213427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01577149424791251,"score_gpt":0.2232374945029549,"score_spread":0.2074660002550423,"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."}}