{"id":"W2564136532","doi":"10.1109/dsaa.2016.67","title":"Informative Priors and Bayesian Computation","year":2016,"lang":"en","type":"article","venue":"","topic":"Gaussian Processes and Bayesian Inference","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; Kelowna General Hospital; University of British Columbia","funders":"","keywords":"Prior probability; Computer science; Prior information; Inference; Bayesian probability; Bayesian inference; Machine learning; Computation; Artificial intelligence; Algorithm","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":[0.00006711062,0.00006558448,0.00006267156,0.00005141972,0.0000576024,0.0001093926,0.0001925433,0.00002393473,0.00001894677],"category_scores_gemma":[0.00001456549,0.00003627116,0.0000110697,0.0001316323,0.0000374005,0.001038437,0.0001059916,0.00002373523,0.00005164164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001021026,"about_ca_system_score_gemma":0.00003346497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003951945,"about_ca_topic_score_gemma":0.000002691226,"domain_scores_codex":[0.9995143,0.00001015141,0.0001159754,0.0001368558,0.00009714805,0.0001255185],"domain_scores_gemma":[0.9996852,0.0000489385,0.00004561916,0.0001095127,0.00004473011,0.00006598148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000001395296,0.000007688596,0.001321149,0.0000119321,0.000004123892,0.000001765902,0.0007528608,8.855505e-7,0.0001235184,0.4240318,0.0004676756,0.5732753],"study_design_scores_gemma":[0.003003196,0.0007369129,0.2297713,0.0003535676,0.00001236986,0.0002247181,0.000453635,0.1628034,0.01406126,0.578172,0.008930488,0.00147711],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003655138,0.00001037524,0.9788973,0.002709066,0.00004416991,0.00005176316,4.480379e-7,0.0001059839,0.01452581],"genre_scores_gemma":[0.9198959,0.00001201619,0.07953686,0.0002772114,0.000008287053,0.000002667025,1.474264e-7,0.000001766634,0.0002650973],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9162408,"threshold_uncertainty_score":0.1479095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006763566499875171,"score_gpt":0.2217822479665868,"score_spread":0.2150186814667117,"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."}}