{"id":"W1499572872","doi":"10.2139/ssrn.1550809","title":"Non-Bayesian Social Learning, Second Version","year":2010,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Opinion Dynamics and Social Influence","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Bayesian probability; Artificial intelligence; Computer science; Psychology; Machine learning","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":[0.005738346,0.002036409,0.004605765,0.002333497,0.001541482,0.005435471,0.004221603,0.005534698,0.07217135],"category_scores_gemma":[0.05673939,0.001550826,0.002459192,0.004375434,0.003456198,0.01084275,0.002558849,0.006020907,0.01096138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00318196,"about_ca_system_score_gemma":0.002966698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01233544,"about_ca_topic_score_gemma":0.01070652,"domain_scores_codex":[0.9958398,0.001637834,0.0002233748,0.001183253,0.0007267153,0.0003889711],"domain_scores_gemma":[0.9709451,0.01971089,0.001502556,0.003567775,0.003614882,0.000658831],"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":[0.0002348066,0.0002426038,0.002741854,0.001175805,0.0004367607,0.0004298605,0.0003632561,0.06064586,0.0005720095,0.7652777,0.09616505,0.07171457],"study_design_scores_gemma":[0.00008882171,0.00004916759,0.001776666,0.0002055688,0.0001063293,0.0001881875,0.00007188351,0.2642216,0.0002154192,0.7213047,0.01168578,0.00008580322],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02630371,0.01212244,0.8685045,0.02649619,0.008032736,0.0004035203,0.008308472,0.001496544,0.04833189],"genre_scores_gemma":[0.6262188,0.02014119,0.1527326,0.005234499,0.01290297,0.002454946,0.007515986,0.001583427,0.1712156],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07217135,"threshold_uncertainty_score":0.2414372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002398126120351418,"score_gpt":0.2328894965191324,"score_spread":0.230491370398781,"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."}}