{"id":"W2043384621","doi":"10.1109/tit.2014.2346183","title":"Tracking a Markov-Modulated Stationary Degree Distribution of a Dynamic Random Graph","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Information Theory","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Markov chain; Mathematics; Stationary distribution; Degree distribution; Markov process; Degree (music); Markov model; Markov kernel; Discrete mathematics; Variable-order Markov model; Algorithm; Applied mathematics; Combinatorics; Statistics; Complex network","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":[0.0004973412,0.0001399405,0.0001987367,0.0002198817,0.0001738187,0.00003310417,0.000119167,0.0000439811,0.0004785181],"category_scores_gemma":[0.000004556578,0.0001372429,0.0001840772,0.0004126788,0.00006418069,0.0006371362,0.000001166003,0.0001562518,0.0000318519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000383793,"about_ca_system_score_gemma":0.0000252749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002665704,"about_ca_topic_score_gemma":0.000004429318,"domain_scores_codex":[0.9989184,0.0001543402,0.0004941289,0.0000969937,0.0001906372,0.0001454702],"domain_scores_gemma":[0.9990646,0.0002319824,0.0002433881,0.0002388446,0.0001788132,0.0000423481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005052069,0.0001990864,0.00005699155,0.00003712116,0.0002684037,6.871558e-8,0.0007360519,0.03583409,0.000451246,0.02282888,0.0002816454,0.9388012],"study_design_scores_gemma":[0.006910888,0.0004194058,0.008481685,0.000307585,0.0006474305,0.000005562895,0.001534504,0.6909901,0.0275126,0.2583283,0.00372677,0.001135205],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05576539,0.000003583088,0.941704,0.00002279463,0.0000800591,0.000214803,0.0002192007,0.0001062528,0.001883944],"genre_scores_gemma":[0.9985274,0.000003525682,0.0007650479,0.00002936335,0.00001520613,0.00005315044,0.0005405767,0.000008481965,0.00005723672],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.942762,"threshold_uncertainty_score":0.5596603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006857078902441537,"score_gpt":0.2326298479569773,"score_spread":0.2257727690545357,"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."}}