{"id":"W2112563055","doi":"10.48550/arxiv.1406.3070","title":"Distributed Parameter Estimation in Probabilistic Graphical Models","year":2014,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; University of British Columbia","funders":"","keywords":"Graphical model; Estimator; Probabilistic logic; Consistency (knowledge bases); Computer science; Estimation theory; Estimation; Mathematical optimization; Algorithm; Theoretical computer science; Data mining; Mathematics; Artificial intelligence; Statistics; Engineering","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":[0.01028566,0.001619229,0.0019931,0.002615604,0.00075899,0.002522493,0.003877368,0.002637692,0.002621042],"category_scores_gemma":[0.0604868,0.001364383,0.001958842,0.003229375,0.003588005,0.006317028,0.003698976,0.005413214,0.0006954177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00165137,"about_ca_system_score_gemma":0.001562895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002191864,"about_ca_topic_score_gemma":0.00144231,"domain_scores_codex":[0.9906668,0.005745551,0.0003172758,0.001398822,0.001522228,0.000349231],"domain_scores_gemma":[0.9578815,0.03631679,0.001629357,0.002489862,0.001370946,0.0003115718],"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":[0.00004667393,0.00003757423,0.0008895457,0.0001531734,0.0001140503,0.0001125685,0.0001697459,0.304634,0.0005635911,0.6592773,0.001266168,0.03273572],"study_design_scores_gemma":[0.00001059487,0.000009746256,0.00009267136,0.00002313765,0.00001758128,0.00003147715,0.00001271138,0.4255487,0.0001812935,0.573232,0.0008272523,0.00001279854],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001097617,0.0001210987,0.9981937,0.0001260473,0.00001122243,0.000005383265,0.00002691669,0.00005775195,0.0003602025],"genre_scores_gemma":[0.361363,0.0023617,0.6307514,0.0005226657,0.0004464785,0.0003528858,0.0007979278,0.000426714,0.002977262],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01028566,"threshold_uncertainty_score":0.05439645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06240903234040149,"score_gpt":0.1874287057094753,"score_spread":0.1250196733690739,"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."}}