{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003204113,0.00009970403,0.000170435,0.00009401365,0.00009585648,0.0002514627,0.0001578858,0.00004297985,2.625445e-7],"category_scores_gemma":[0.000005804942,0.00008977701,0.00004835513,0.0004647863,0.00002963229,0.0006170459,0.0000136453,0.0001067193,0.000005219572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002973372,"about_ca_system_score_gemma":0.00001190147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005509314,"about_ca_topic_score_gemma":0.000001897122,"domain_scores_codex":[0.9989892,0.00007656093,0.0003131058,0.0002459282,0.0001761874,0.0001990141],"domain_scores_gemma":[0.9993147,0.0002833769,0.0001285996,0.0001704399,0.00005265583,0.00005021859],"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":[0.00001780549,0.00002222959,0.0003300401,0.0001563988,0.00008552452,0.00001082569,0.0001357567,0.8120243,0.06250273,0.04412951,0.01093674,0.06964814],"study_design_scores_gemma":[0.0002626604,0.00002812939,0.001296533,0.00003731522,0.00001936247,0.00002734809,0.000004638651,0.9956012,0.00006580468,0.00008367326,0.002484848,0.00008853784],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07823845,0.001323664,0.915742,0.00237526,0.00176052,0.0003770173,0.000004413759,0.0001403604,0.00003830751],"genre_scores_gemma":[0.9984849,0.00001821909,0.0006130412,0.0003839452,0.0004268071,0.00005114367,0.000003816864,0.000007913479,0.00001022348],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9202464,"threshold_uncertainty_score":0.3661,"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."}}