{"id":"W4402679615","doi":"10.1108/jfbm-08-2024-0191","title":"Key drivers of green innovation in family firms: a machine learning approach","year":2024,"lang":"en","type":"article","venue":"Journal of Family Business Management","topic":"Family Business Performance and Succession","field":"Business, Management and Accounting","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Key (lock); Business; Marketing; Process management; Computer science; Industrial organization; Computer security","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001374041,0.0003360642,0.0005654846,0.00370208,0.0001073388,0.0002936337,0.0005415362,0.0001153468,0.00003053564],"category_scores_gemma":[0.00005799517,0.0002746396,0.0001402929,0.006548387,0.00008113051,0.003204475,0.0003122187,0.0004789724,0.00003866795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001214381,"about_ca_system_score_gemma":0.00006412362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007109214,"about_ca_topic_score_gemma":0.00001644868,"domain_scores_codex":[0.9969898,0.00002321466,0.001412788,0.0003293338,0.0008773989,0.0003674763],"domain_scores_gemma":[0.9981083,0.0000322306,0.0008327632,0.0002323883,0.0007792589,0.00001508787],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001571398,0.002095148,0.2146839,0.03028224,0.001073934,0.001950822,0.00195229,0.1266766,0.01525828,0.04508596,0.01789211,0.5414774],"study_design_scores_gemma":[0.002995858,0.00005573419,0.7567817,0.003556957,0.0003272197,0.00001905423,0.003519385,0.1062044,0.00002992949,0.001811156,0.123962,0.0007365932],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9705666,0.00193819,0.006537398,0.0006153017,0.001359516,0.000352955,0.000002101908,0.00008557204,0.0185424],"genre_scores_gemma":[0.9958696,0.0009350677,0.001283473,0.0006952062,0.0006352052,0.00001252106,0.00004600752,0.00005557952,0.0004672904],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5420979,"threshold_uncertainty_score":0.9999706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02526966586476768,"score_gpt":0.2378808749386417,"score_spread":0.212611209073874,"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."}}