{"id":"W2931195386","doi":"10.1103/physreve.99.032222","title":"Determining the number of integrals of motion by an adapted correlation dimension method","year":2019,"lang":"en","type":"article","venue":"Physical review. E","topic":"Quantum chaos and dynamical systems","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation; Deutscher Akademischer Austauschdienst; Compute Canada","keywords":"Correlation dimension; Phase space; Integrable system; Dimension (graph theory); Chaotic; Hamiltonian system; Statistical physics; Correlation integral; Hamiltonian (control theory); Classical mechanics; Motion (physics); Correlation; Physics; Mathematics; Mathematical analysis; Computer science; Quantum mechanics; Geometry; Mathematical optimization; Pure mathematics; Artificial intelligence","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":[0.001531753,0.0004334573,0.0004595906,0.001468223,0.0005432148,0.0007412183,0.001006396,0.0006004018,0.002092704],"category_scores_gemma":[0.005688579,0.000267324,0.0005039786,0.0007291051,0.0009774189,0.001533574,0.000853223,0.0009273293,0.0002949678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000810869,"about_ca_system_score_gemma":0.001325383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002482034,"about_ca_topic_score_gemma":0.00280154,"domain_scores_codex":[0.9995505,0.0001571475,0.00002601616,0.00005075503,0.0001646831,0.00005090691],"domain_scores_gemma":[0.997198,0.001704676,0.0001917488,0.0003294981,0.000445307,0.0001307339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002392635,0.0001195177,0.004966537,0.0001094917,0.000102971,0.000358129,0.000167861,0.6268771,0.01692286,0.2820812,0.001990285,0.06606479],"study_design_scores_gemma":[0.000005781783,0.000007630492,0.0002010953,0.000002902983,0.000002007488,0.00001740411,0.000004426971,0.9890977,0.0007054009,0.009726048,0.0002225406,0.000007032287],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08357374,0.0001150912,0.9124742,0.00009723495,0.00004110725,0.00005860264,0.0000714967,0.0003192672,0.003249254],"genre_scores_gemma":[0.4592843,0.0001090913,0.5380966,0.00006134844,0.0000245673,0.0001786456,0.0001719716,0.0001843987,0.001889001],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002482034,"threshold_uncertainty_score":0.008100748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01368262686829724,"score_gpt":0.3478445972420434,"score_spread":0.3341619703737462,"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."}}