{"id":"W2997954700","doi":"10.6000/1929-7092.2019.08.96","title":"Factors Influencing the Quality of Decision-Making Using Business Intelligence in a Metal Rolling Plant in KwaZulu-Natal","year":2019,"lang":"en","type":"article","venue":"Journal of Reviews on Global Economics","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Quality (philosophy); Business","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009410931,0.0001867113,0.0002731408,0.0007547148,0.001704517,0.002316184,0.0007648512,0.0004557864,0.002648277],"category_scores_gemma":[0.004950294,0.000299322,0.0002579046,0.001255065,0.001139643,0.0007151295,0.001061405,0.0009450822,0.0003456242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004644799,"about_ca_system_score_gemma":0.00432344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2298332,"about_ca_topic_score_gemma":0.4073327,"domain_scores_codex":[0.9989524,0.0003416845,0.00006865089,0.00008190313,0.0001471308,0.0004082606],"domain_scores_gemma":[0.9960139,0.001566961,0.001046704,0.0001038631,0.0006148617,0.000653714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004975742,0.0007352891,0.9420178,0.0001163325,0.00008907198,0.003405563,0.03520207,0.001206322,0.002486258,0.001429473,0.0006060494,0.0122082],"study_design_scores_gemma":[0.00001271318,0.0002021148,0.9122782,0.00007124818,0.00003148896,0.0003007193,0.08359225,0.001736266,0.0003884932,0.0001891977,0.001161337,0.00003592615],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990921,0.00001830331,0.00004637895,0.0001723377,0.000002002299,0.000009348416,0.00002801572,0.000001294782,0.0006301999],"genre_scores_gemma":[0.9994829,0.00002290239,0.00005869153,0.00001729323,7.429571e-7,0.000005642493,0.0000252603,8.480436e-7,0.0003856562],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2298332,"threshold_uncertainty_score":0.4569908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1424749030764058,"score_gpt":0.3637077339797366,"score_spread":0.2212328309033308,"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."}}