{"id":"W3122868537","doi":"10.2139/ssrn.3649934","title":"Bayesian Nonparametric Forecast Pooling","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Pooling; Bayesian probability; Nonparametric statistics; Econometrics; Computer science; Artificial intelligence; Statistics; 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":[0.001470717,0.0001848204,0.0002354598,0.0001607268,0.0002236713,0.0002360008,0.001135072,0.00008360278,0.00001165454],"category_scores_gemma":[0.0001335654,0.0001586123,0.0001722064,0.0009785357,0.0000213027,0.0005169554,0.0001342554,0.001927149,0.00004039683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002622176,"about_ca_system_score_gemma":0.001261589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000821485,"about_ca_topic_score_gemma":0.00001363584,"domain_scores_codex":[0.9966811,0.0001503876,0.0003055439,0.0003565114,0.000322977,0.002183514],"domain_scores_gemma":[0.9991511,0.00006681688,0.0001532188,0.000256043,0.00007595383,0.0002968702],"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":[0.000009498702,0.00001750039,0.00006527267,0.000003600992,0.00004482405,0.00001479186,0.0002602825,0.00004861417,0.0002168768,0.5702427,0.0001459109,0.4289301],"study_design_scores_gemma":[0.0005600209,0.0004640399,0.00005197936,0.00001121715,0.00001985289,0.0009588367,0.00007551663,0.1237029,0.0003119308,0.8709826,0.002552561,0.0003085142],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001197522,0.002169504,0.988001,0.006144066,0.0002186169,0.00008711602,4.297772e-7,0.00009707544,0.002084657],"genre_scores_gemma":[0.7706465,0.0007286262,0.2265395,0.001483849,0.0003941381,0.000002238177,3.93562e-7,0.00001953765,0.0001852083],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.769449,"threshold_uncertainty_score":0.8372611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01539201792725261,"score_gpt":0.2473419823257859,"score_spread":0.2319499643985333,"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."}}