{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006318246,0.0006901908,0.0005211771,0.0004745998,0.0003119337,0.0003988017,0.0007861148,0.0005831801,0.003335582],"category_scores_gemma":[0.001811471,0.0002994756,0.0004627664,0.0005549727,0.0004012484,0.0006961806,0.0005345672,0.0007937102,0.001044839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003001192,"about_ca_system_score_gemma":0.0009091915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004550909,"about_ca_topic_score_gemma":0.004560699,"domain_scores_codex":[0.9997475,0.00007467665,0.00001971095,0.00006172182,0.00006442467,0.00003196932],"domain_scores_gemma":[0.9996092,0.0001381805,0.00003678057,0.0000585485,0.0001388398,0.00001850454],"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":[0.00009080049,0.00004504314,0.0006389975,0.0001129475,0.00005873819,0.00005086902,0.0000827543,0.4927369,0.01364736,0.007601099,0.002089885,0.4828446],"study_design_scores_gemma":[0.000007265162,0.00003566887,0.0001045748,0.000006336902,0.000005684486,0.00002430193,0.00000712997,0.9929416,0.003551378,0.002192305,0.001116818,0.000006916735],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01263505,0.0002798101,0.9842423,0.00005716884,0.00003907144,0.00005223717,0.00005340189,0.0009834042,0.001657623],"genre_scores_gemma":[0.3483924,0.0004180642,0.645989,0.0001114977,0.00004618541,0.0003494291,0.0004075025,0.0001964767,0.004089445],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004550909,"threshold_uncertainty_score":0.0111587,"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."}}