{"id":"W4403331479","doi":"10.1109/lcsys.2024.3478272","title":"Computation and Formal Verification of Neural Network Contraction Metrics","year":2024,"lang":"en","type":"article","venue":"IEEE Control Systems Letters","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Computer science; Computation; Artificial neural network; Formal verification; Contraction (grammar); Programming language; Artificial intelligence; Theoretical computer science; Medicine; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00333945,0.0007189421,0.0005727281,0.0006238897,0.0006212516,0.001832048,0.001483287,0.0008850452,0.003302639],"category_scores_gemma":[0.01767596,0.0004439872,0.0008731426,0.0003677967,0.002861236,0.002366644,0.00276706,0.002075978,0.0003469159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001613549,"about_ca_system_score_gemma":0.002450241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002218784,"about_ca_topic_score_gemma":0.001820076,"domain_scores_codex":[0.9977648,0.0006435208,0.0001432925,0.0003734753,0.0009106371,0.0001642709],"domain_scores_gemma":[0.99431,0.003159901,0.0004743125,0.0008914717,0.001065959,0.00009829732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002986,0.00002389417,0.0005360715,0.00007330027,0.00001743104,0.0001587912,0.0001151066,0.4870445,0.004876276,0.4894629,0.0005041045,0.01715777],"study_design_scores_gemma":[0.000006074018,0.00001414729,0.00003708533,0.000008968149,0.00000195776,0.00001884623,0.00001280003,0.9221219,0.002590139,0.0746825,0.0004998772,0.000005749975],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01787452,0.00002539203,0.9788238,0.0001496159,0.00002311781,0.00004535694,0.0000555103,0.0002263195,0.002776309],"genre_scores_gemma":[0.6632409,0.00008967129,0.3335875,0.00009915487,0.00002591924,0.0002238523,0.0002073145,0.0002452605,0.002280383],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00333945,"threshold_uncertainty_score":0.01766092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01321767362352733,"score_gpt":0.2347930273945864,"score_spread":0.221575353771059,"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."}}