{"id":"W4400641805","doi":"10.36227/techrxiv.24495202.v2","title":"Subspace Rotation Algorithm for Training Restricted Hopfield Network","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Railway Engineering and Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Subspace topology; Training (meteorology); Algorithm; Computer science; Rotation (mathematics); Artificial intelligence; Hopfield network; Artificial neural network; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000117324,0.0003126764,0.0002983024,0.000134281,0.00003399303,0.0001328156,0.000158974,0.0004370305,0.00001258044],"category_scores_gemma":[0.00002592088,0.0003332388,0.0001620552,0.0002042862,0.000008341088,0.00002586909,0.00009683314,0.0007414063,0.00001672081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009091193,"about_ca_system_score_gemma":0.00004900196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001578085,"about_ca_topic_score_gemma":0.00001899578,"domain_scores_codex":[0.9989029,0.000006900946,0.0002736186,0.0003076153,0.000125325,0.000383655],"domain_scores_gemma":[0.9994322,0.0001340694,0.00002468527,0.0002829498,0.00004408839,0.00008197332],"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":[0.000001225443,0.000002020656,0.000001138511,0.0003100399,0.00009975529,0.000004360362,0.0002337023,0.891679,0.00001946867,0.0008309666,0.01106763,0.09575067],"study_design_scores_gemma":[0.0001097795,0.00001682737,0.00002407589,0.0002135705,0.0000595772,0.000003317023,0.00006737116,0.9884821,0.00003454033,0.007226044,0.003392103,0.0003707047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00202721,0.001341632,0.9806048,0.000102103,0.00500107,0.000478186,0.0001001245,0.002745751,0.007599109],"genre_scores_gemma":[0.1266923,0.000659641,0.8603318,0.00006419295,0.004349772,0.0008030646,0.001123856,0.0004887339,0.005486618],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1246651,"threshold_uncertainty_score":0.999912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01580763214690722,"score_gpt":0.2287873983696369,"score_spread":0.2129797662227297,"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."}}