{"id":"W2907511104","doi":"10.1145/3302504.3313354","title":"Invariant, viability and discriminating kernel under-approximation via zonotope scaling","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reachability; Scaling; Invariant (physics); Parametric statistics; Affine transformation; Kernel (algebra); Scalability; Computer science; Nonlinear system; Model predictive control; Regular polygon; Mathematical optimization; Control theory (sociology); Algorithm; Mathematics; Artificial intelligence; Discrete mathematics; Control (management); Pure mathematics","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":[0.0008102094,0.0004864165,0.0006362007,0.0006575765,0.000470574,0.001188792,0.000867601,0.0005407321,0.002144383],"category_scores_gemma":[0.003464095,0.0003030586,0.0007311842,0.0004421325,0.001468271,0.001542562,0.001792362,0.001068151,0.0002970047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007509993,"about_ca_system_score_gemma":0.0005399931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001020572,"about_ca_topic_score_gemma":0.0008704943,"domain_scores_codex":[0.999429,0.0001426173,0.00002993284,0.000115013,0.0001968943,0.00008648997],"domain_scores_gemma":[0.9989904,0.0004972707,0.0001258483,0.0002180651,0.0001126371,0.00005578637],"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":[0.0001389255,0.00004657274,0.00120719,0.00008142028,0.00002763731,0.0001520873,0.0002326729,0.3659152,0.01259024,0.57798,0.0006263375,0.04100177],"study_design_scores_gemma":[0.00001179259,0.00004860167,0.0002175709,0.000009379252,0.000006120396,0.00004454002,0.00003083617,0.8495196,0.003913007,0.1452288,0.0009548603,0.00001484058],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04802907,0.0000485064,0.9493998,0.00004544733,0.000007219011,0.00002536547,0.00003997425,0.0001734204,0.002231163],"genre_scores_gemma":[0.82013,0.00008602677,0.1774839,0.0000355981,0.00001113111,0.0001035954,0.0001547835,0.0001046861,0.001890278],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002144383,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04830138435669108,"score_gpt":0.3049434866517462,"score_spread":0.2566421022950551,"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."}}