{"id":"W4293519282","doi":"10.1109/cibcb55180.2022.9863054","title":"EvoDNN - Evolving Weights, Biases, and Activation Functions in a Deep Neural Network","year":2022,"lang":"en","type":"article","venue":"","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Activation function; Computer science; Differentiable function; Artificial neural network; Artificial intelligence; Deep neural networks; Set (abstract data type); Flexibility (engineering); Feature (linguistics); Coding (social sciences); Function (biology); Code (set theory); Theoretical computer science; Mathematics; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001394434,0.00006376656,0.00006047412,0.00008462418,0.0005559655,0.00005679892,0.0002074961,0.0000147765,0.0001402639],"category_scores_gemma":[0.00001188228,0.00006382179,0.00001979365,0.0007819637,0.00001671321,0.0004524336,0.0002960765,0.0001409363,0.000005170666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006946276,"about_ca_system_score_gemma":0.00002649583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001416525,"about_ca_topic_score_gemma":0.00004483909,"domain_scores_codex":[0.9992629,0.00005237096,0.0001297914,0.0002500974,0.0001391295,0.000165709],"domain_scores_gemma":[0.9995525,0.0001352343,0.00003642257,0.0002125656,0.00002142561,0.00004179657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009808533,0.0004300367,0.02761388,0.000007224648,0.00002085909,0.000009309915,0.0007671511,0.2162174,0.0003705081,0.6373267,0.02177487,0.09545228],"study_design_scores_gemma":[0.0001303248,0.00003153636,0.07163657,0.000002248175,0.000001392253,0.00001739796,0.00008641288,0.9137461,0.000004400278,0.007257449,0.007000695,0.00008547324],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08094715,0.000549474,0.908055,0.006293109,0.0002812184,0.0003128849,0.000003377575,0.0002323047,0.003325482],"genre_scores_gemma":[0.9642604,0.000005636519,0.03451543,0.0003908319,0.00009374491,0.0001797554,0.00001631283,0.000004616221,0.0005332452],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8833133,"threshold_uncertainty_score":0.4276093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01799613487483072,"score_gpt":0.2302230516953342,"score_spread":0.2122269168205034,"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."}}