{"id":"W4367852399","doi":"10.1093/pnasnexus/pgad150","title":"Dimension reduction of dynamics on modular and heterogeneous directed networks","year":2023,"lang":"en","type":"article","venue":"PNAS Nexus","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund; Université Laval","keywords":"Adjacency matrix; Observable; Dynamical systems theory; Computer science; Dimension (graph theory); Modular design; Reduction (mathematics); Network dynamics; System dynamics; Theoretical computer science; Ode; Representation (politics); Mathematics; Graph; Applied mathematics; Artificial intelligence; Discrete mathematics; 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":[0.000691361,0.0004811365,0.0003941724,0.0008163693,0.0003222702,0.0007537212,0.0004823499,0.0003613598,0.0009588877],"category_scores_gemma":[0.003015058,0.0002495975,0.0007673852,0.0003953454,0.0009404079,0.001140033,0.0009769873,0.0007485307,0.0001448842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008700494,"about_ca_system_score_gemma":0.0004836236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002048731,"about_ca_topic_score_gemma":0.001772324,"domain_scores_codex":[0.9996518,0.0001643468,0.00001618539,0.00006859748,0.0000700445,0.00002897357],"domain_scores_gemma":[0.9990273,0.0005204263,0.0001661526,0.0001431033,0.00008853456,0.00005457057],"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":[0.00002086995,0.00002055053,0.001204645,0.00005722424,0.00005211121,0.0001026499,0.0001613761,0.608682,0.004337667,0.3693258,0.0008185322,0.01521651],"study_design_scores_gemma":[0.000003117597,0.000006268155,0.0002357275,0.000004255085,0.000003911719,0.00001565677,0.00001186664,0.9060215,0.0003882064,0.0927289,0.000574753,0.000005886455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0748786,0.000229811,0.9215286,0.000276841,0.00003236369,0.00004456204,0.0001402191,0.0001293929,0.002739583],"genre_scores_gemma":[0.7939104,0.0006883194,0.2001765,0.000114084,0.0001079709,0.0002751019,0.000363329,0.0001061075,0.004258223],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002048731,"threshold_uncertainty_score":0.006312668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009167344276582053,"score_gpt":0.2423694599239576,"score_spread":0.2332021156473755,"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."}}