{"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":"codex-gemma-dda1882f352a","candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.006311739,0.0002184588,0.0002770956,0.001234186,0.000475456,0.0006403955,0.0006268637,0.0001378808,0.0002324583],"category_scores_gemma":[0.0002326154,0.0001743012,0.0000721469,0.002711038,0.00008884935,0.003644657,0.0002002153,0.002537888,0.0007760755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004762528,"about_ca_system_score_gemma":0.0007707116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004155261,"about_ca_topic_score_gemma":0.0009926668,"domain_scores_codex":[0.9954236,0.00008890246,0.0004704269,0.0003051129,0.0005533065,0.003158641],"domain_scores_gemma":[0.998686,0.00007233512,0.0001601539,0.000262262,0.000795853,0.00002341285],"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":[0.0001622455,0.0004157885,0.1646643,0.000224668,0.00007774853,0.00003195891,0.0001249133,0.0004605204,0.01506778,0.09847538,0.007682201,0.7126126],"study_design_scores_gemma":[0.00163296,0.00003984886,0.3726457,0.0002417031,0.00002019695,0.00006075433,0.005282443,0.01075113,0.00004465105,0.5802753,0.02840626,0.0005990306],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9408805,0.002430351,0.02527514,0.004304121,0.000844088,0.0004605344,1.555165e-7,0.00009120927,0.02571385],"genre_scores_gemma":[0.9938472,0.001653481,0.0008723597,0.000894959,0.001615496,0.00004393382,0.000005966143,0.00005021993,0.001016371],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7120135,"threshold_uncertainty_score":0.9997633,"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."}}