{"id":"W3167805910","doi":"","title":"Parallelizing Legendre Memory Unit Training","year":2021,"lang":"en","type":"article","venue":"UWSpace (University of Waterloo)","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Recurrent neural network; Leverage (statistics); Machine translation; Artificial intelligence; Benchmark (surveying); Inference; Transformer; Machine learning; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006501201,0.00007287255,0.0001262282,0.00004351098,0.0002034082,0.00003003797,0.0004794946,0.00004030463,0.00006686156],"category_scores_gemma":[0.000002412716,0.00008644743,0.0000708387,0.0003196422,0.00004862652,0.0003009076,0.0002460719,0.00009523422,0.00003685692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001068298,"about_ca_system_score_gemma":0.00005200077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007314762,"about_ca_topic_score_gemma":0.001998483,"domain_scores_codex":[0.999354,0.00003586549,0.00005625722,0.0002441861,0.0001208487,0.0001888098],"domain_scores_gemma":[0.9994141,0.00002927618,0.00005250403,0.0003533683,0.00007320437,0.00007754692],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0000253381,0.000318115,0.001443597,0.0001252395,0.0002211174,0.001218182,0.30478,0.007011039,0.08064558,0.3402475,0.01686207,0.2471022],"study_design_scores_gemma":[0.005349054,0.000383181,0.02006842,0.0004637401,0.0002102081,0.0004252645,0.5429334,0.1888945,0.05370484,0.01626424,0.1685258,0.002777352],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9580196,0.0001533067,0.02530855,0.01455913,0.0001227079,0.00007987303,0.00000365418,0.0001350227,0.001618132],"genre_scores_gemma":[0.8131014,0.00009388477,0.05983795,0.0001951444,0.00005225732,2.737467e-7,0.00001020797,0.000008025634,0.1267009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3239833,"threshold_uncertainty_score":0.3525224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03373950590677315,"score_gpt":0.2117834451219137,"score_spread":0.1780439392151406,"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."}}