{"id":"W2996414141","doi":"10.28945/4462","title":"What Can Executives Take From Social Capital Theory?","year":2019,"lang":"en","type":"article","venue":"Muma Business Review","topic":"Knowledge Management and Sharing","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Toronto","keywords":"Social capital; Field (mathematics); Capital (architecture); Individual capital; Business; Organizational capital; Knowledge management; Economic capital; Public relations; Economics; Human capital; Sociology; Political science; Computer science; Finance; Intellectual capital; Economic growth; Social science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006611969,0.0001460176,0.0003625583,0.00003981365,0.000346314,0.0002941869,0.0004024378,0.00006071703,0.005134793],"category_scores_gemma":[0.0001469751,0.0001288674,0.0001096773,0.0004552862,0.0001297753,0.0006261972,0.0001310598,0.00009009863,0.001284762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006743868,"about_ca_system_score_gemma":0.00007664366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006486458,"about_ca_topic_score_gemma":0.0009394303,"domain_scores_codex":[0.9986465,0.0002456656,0.0002142997,0.0002889559,0.0003043704,0.0003001816],"domain_scores_gemma":[0.9994085,0.00007894725,0.0001128721,0.0001945347,0.0001524884,0.00005268565],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002008854,0.000176381,0.005126938,0.002953002,0.0001690772,0.0000242953,0.06806631,6.593968e-7,0.00003995579,0.2870351,0.01437082,0.6220174],"study_design_scores_gemma":[0.0002973324,0.000006002541,0.03261701,0.003737275,0.0001285819,2.160139e-7,0.01032356,0.000003388676,0.000004689793,0.007297765,0.9451519,0.0004322367],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.348103,0.3356399,0.0000985032,0.0126246,0.005339361,0.002085967,0.00002078845,0.0002940377,0.2957939],"genre_scores_gemma":[0.8031744,0.162407,0.0000523914,0.001874448,0.00133189,0.00006233493,0.00007959742,0.00003886777,0.03097899],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9307811,"threshold_uncertainty_score":0.9994928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03087009733181928,"score_gpt":0.3043774632098588,"score_spread":0.2735073658780395,"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."}}