{"id":"W4385489627","doi":"10.1007/978-3-031-33390-3_14","title":"Neural Networks","year":2023,"lang":"en","type":"book-chapter","venue":"Statisctics and computing/Statistics and computing","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Initialization; Backpropagation; Artificial neural network; Normalization (sociology); Regularization (linguistics); Gradient descent; Stochastic gradient descent; Computer science; Artificial intelligence; Feedforward neural network; Nonlinear system; Dropout (neural networks); Feed forward; Algorithm; Mathematics; Pattern recognition (psychology); Machine learning","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":[0.000273611,0.0006537953,0.0005068755,0.0006265496,0.0003145273,0.001474358,0.0009222092,0.001011684,0.02768208],"category_scores_gemma":[0.001330028,0.0002931022,0.0002995481,0.0008008624,0.0004233866,0.001430955,0.0007060664,0.001050023,0.01235843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004815368,"about_ca_system_score_gemma":0.000482152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00181597,"about_ca_topic_score_gemma":0.002570614,"domain_scores_codex":[0.9997796,0.00002974417,0.0000106181,0.00005879845,0.000103833,0.00001737303],"domain_scores_gemma":[0.9997769,0.00006536149,0.00001403816,0.00005029078,0.00008301112,0.00001028432],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003991209,0.00003453557,0.0003162027,0.0002693038,0.00005321874,0.00007107152,0.00003700966,0.06183505,0.00321598,0.1551064,0.06662439,0.7123969],"study_design_scores_gemma":[0.00001635558,0.00005375806,0.0006491442,0.0002112584,0.00005865113,0.0002667152,0.00004675024,0.427835,0.007026293,0.2570624,0.3067362,0.00003748764],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.006609493,0.01819362,0.6631457,0.002377307,0.002635745,0.0001114135,0.001183634,0.002558974,0.3031841],"genre_scores_gemma":[0.1852287,0.01906555,0.2273573,0.001300247,0.001378475,0.0003191285,0.002794788,0.0007154063,0.5618404],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.02768208,"threshold_uncertainty_score":0.09260583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02097023155890035,"score_gpt":0.2522566464519125,"score_spread":0.2312864148930122,"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."}}