{"id":"W2094042625","doi":"10.2139/ssrn.2369278","title":"Bayesian Methods in Family Business Research","year":2013,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Family Business Performance and Succession","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Family business; Bayesian probability; Econometrics; Data science; Computer science; Business; Artificial intelligence; Economics; Marketing","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":[0.05782855,0.001556846,0.004319224,0.007237846,0.002116669,0.003993084,0.003950359,0.004168951,0.008139536],"category_scores_gemma":[0.162687,0.002185309,0.002080484,0.008424127,0.005191885,0.007489044,0.003342572,0.006359673,0.001165715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003308753,"about_ca_system_score_gemma":0.004937001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02189436,"about_ca_topic_score_gemma":0.01842634,"domain_scores_codex":[0.965199,0.0302893,0.0006664224,0.001450366,0.001983021,0.0004119154],"domain_scores_gemma":[0.7314858,0.2551483,0.002947965,0.005009755,0.004209713,0.001198358],"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":[0.0001152861,0.0002015849,0.003031962,0.0004823566,0.0005417372,0.0001313674,0.0006567767,0.1044023,0.0001266832,0.7659976,0.005164338,0.1191478],"study_design_scores_gemma":[0.00005453796,0.00002635599,0.0006107942,0.0001524878,0.0000458744,0.00004340965,0.00008512704,0.1198768,0.0000574207,0.8745316,0.004480531,0.00003502657],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004111323,0.006391677,0.9851836,0.001394881,0.0001351207,0.00008147751,0.0001381055,0.0001069036,0.002456911],"genre_scores_gemma":[0.2014864,0.01468962,0.7683284,0.0008412109,0.001332115,0.001460567,0.0007514836,0.0002448934,0.01086527],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05782855,"threshold_uncertainty_score":0.3058302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03590275338968166,"score_gpt":0.3404092034748355,"score_spread":0.3045064500851539,"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."}}