{"id":"W2165091599","doi":"10.48550/arxiv.1207.1375","title":"Nonparametric Bayesian Logic","year":2012,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Syntax; Inference; Bayesian inference; Artificial intelligence; Dirichlet distribution; Matching (statistics); Dirichlet process; Generative model; Bayesian probability; Generative grammar; Machine learning; Latent Dirichlet allocation; Selection (genetic algorithm); Theoretical computer science; Data mining; Topic model; Mathematics","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":[0.0004001222,0.0001529569,0.0001628323,0.0002357985,0.0001279478,0.00004715996,0.0008617794,0.0001022803,0.00005125816],"category_scores_gemma":[0.00003658589,0.0001517662,0.0001082045,0.00150117,0.00005090479,0.000905141,0.0002470107,0.0001636828,0.0002153462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006476717,"about_ca_system_score_gemma":0.00003182126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001756781,"about_ca_topic_score_gemma":0.000001766773,"domain_scores_codex":[0.9987924,0.0001504405,0.0001025947,0.0004061343,0.00006269337,0.0004857405],"domain_scores_gemma":[0.9988105,0.000110908,0.00007058789,0.0006729578,0.00004746636,0.0002875892],"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":[0.000003723796,0.00007607934,0.003103634,0.000004717241,0.00001246868,0.00003683811,0.00009251775,0.0002179355,0.00005007645,0.9875515,0.0003451188,0.008505394],"study_design_scores_gemma":[0.001031781,0.0001628742,0.009386369,0.00002011433,0.00006996468,0.00006705844,0.00004747262,0.4387146,0.001118166,0.5407279,0.00763067,0.00102309],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01124878,0.0001285638,0.9657655,0.00009650875,0.0003600972,0.00008945663,8.354584e-7,0.000172409,0.0221378],"genre_scores_gemma":[0.8561784,0.00002877779,0.1419052,0.0003447289,0.00007551364,2.325399e-7,5.623875e-7,0.000007264162,0.001459307],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8449296,"threshold_uncertainty_score":0.6188844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07321097545028427,"score_gpt":0.203399019088266,"score_spread":0.1301880436379817,"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."}}