{"id":"W2567674080","doi":"","title":"A Study of Approximate Inference in Probabilistic Relational Models","year":2010,"lang":"en","type":"article","venue":"Asian Conference on Machine Learning","topic":"Opinion Dynamics and Social Influence","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Inference; Computer science; Probabilistic logic; Theoretical computer science; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000226522,0.0001366786,0.0002119976,0.00009377269,0.00009521886,0.00003756535,0.000170674,0.00004515581,0.0002277295],"category_scores_gemma":[0.00006426238,0.000132033,0.0000362715,0.0001760027,0.00005551676,0.0001355122,0.00005597159,0.0008197143,0.000009279064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009109156,"about_ca_system_score_gemma":0.00009290379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007017723,"about_ca_topic_score_gemma":0.0002731015,"domain_scores_codex":[0.9989985,0.00009270576,0.0002956942,0.0002468827,0.0001884754,0.0001777292],"domain_scores_gemma":[0.9994088,0.0001076157,0.0001658193,0.0001762355,0.00008991056,0.00005163942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001157451,0.0003301968,0.2955438,0.000005715382,0.00001020894,0.000001001261,0.002833019,0.0252262,0.0001082245,0.6684113,2.938935e-7,0.007518414],"study_design_scores_gemma":[0.0009135844,0.0002802804,0.06427588,0.00005291192,0.000008101,2.251082e-7,0.002461795,0.8277509,0.000007216493,0.1039833,0.00002256497,0.0002432369],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9572402,0.000001153947,0.002662877,0.0001290857,0.000068136,0.0002913937,0.00001017711,0.00002011713,0.03957682],"genre_scores_gemma":[0.9993746,4.830273e-7,0.0003782639,0.000006870163,0.00003300176,0.00003570729,0.0000240872,0.00001130548,0.0001356281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8025247,"threshold_uncertainty_score":0.5384148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03307190487762339,"score_gpt":0.3031102335139692,"score_spread":0.2700383286363457,"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."}}