{"id":"W2984898617","doi":"10.1080/08853134.2019.1680294","title":"An introduction to an old acquaintance: using Bayesian inference in sales research","year":2019,"lang":"en","type":"article","venue":"Journal of Personal Selling and Sales Management","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Inference; Bayesian inference; Bayesian probability; Psychology; Econometrics; Computer science; Marketing; Business; Economics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01753816,0.001092666,0.001221981,0.003621269,0.003327323,0.007711777,0.002510604,0.007152639,0.01253142],"category_scores_gemma":[0.06960705,0.001162022,0.001246525,0.005130167,0.009718613,0.01641953,0.003679785,0.01499339,0.005787965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002633469,"about_ca_system_score_gemma":0.002773431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005825806,"about_ca_topic_score_gemma":0.0075525,"domain_scores_codex":[0.9893114,0.006803928,0.0006829737,0.0009187016,0.002090932,0.0001919852],"domain_scores_gemma":[0.9017408,0.08808212,0.001621188,0.002524294,0.005078733,0.0009528807],"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":[0.00006503045,0.000132848,0.002986874,0.001084793,0.00009647114,0.0003954573,0.004326351,0.002074595,0.0004849668,0.5368056,0.2598907,0.1916562],"study_design_scores_gemma":[0.00001997309,0.00006843907,0.001542734,0.001851721,0.00003006528,0.0005399886,0.0008224971,0.003539752,0.0002892587,0.4617938,0.5293841,0.0001177864],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003394323,0.1621882,0.4144064,0.3152558,0.02575759,0.0003151208,0.0009098725,0.0006710643,0.07710154],"genre_scores_gemma":[0.1024197,0.2265487,0.4117095,0.1097257,0.09447501,0.001105437,0.0007058182,0.001308206,0.05200194],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01753816,"threshold_uncertainty_score":0.09275174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04886382245410262,"score_gpt":0.3358304481891835,"score_spread":0.2869666257350809,"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."}}