{"id":"W2963398635","doi":"","title":"Scalable MCMC for Mixed Membership Stochastic Blockmodels","year":2016,"lang":"en","type":"article","venue":"UvA-DARE (University of Amsterdam)","topic":"Markov Chains and Monte Carlo Methods","field":"Mathematics","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Markov chain Monte Carlo; Scalability; Inference; Computer science; Mathematical optimization; Algorithm; Markov chain; Monte Carlo method; Applied mathematics; Mathematics; Artificial intelligence; Machine learning; Bayesian probability; Statistics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.003276755,0.001169188,0.001695898,0.0009546043,0.0009791296,0.001294628,0.003639322,0.001848079,0.004629498],"category_scores_gemma":[0.01482224,0.0009534105,0.001178289,0.001195584,0.001460205,0.002207857,0.002437832,0.002851151,0.00107088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001654794,"about_ca_system_score_gemma":0.003428191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01476576,"about_ca_topic_score_gemma":0.02256961,"domain_scores_codex":[0.9984685,0.0006896741,0.00005976883,0.0003081447,0.0003438815,0.0001301278],"domain_scores_gemma":[0.99343,0.004792686,0.0003458022,0.0006189734,0.000530337,0.0002822455],"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":[0.00009793321,0.00006105112,0.0009961932,0.000098732,0.00009453907,0.00008907172,0.00008888122,0.8684691,0.001247328,0.07861505,0.0027047,0.04743737],"study_design_scores_gemma":[0.000006389754,0.000003046851,0.00002432248,0.000002378016,0.000002223701,0.00000463597,0.000001874216,0.9864689,0.0001194441,0.01312415,0.0002396361,0.000002858059],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004298655,0.0001212834,0.9943393,0.0001284676,0.00002252612,0.00004279198,0.000097379,0.0004435141,0.000506045],"genre_scores_gemma":[0.2264536,0.000239007,0.7685019,0.0002620594,0.0001073338,0.000477776,0.001034267,0.0005005971,0.002423282],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01476576,"threshold_uncertainty_score":0.02935964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06906443377149273,"score_gpt":0.2839353260507567,"score_spread":0.214870892279264,"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."}}