{"id":"W2767008766","doi":"10.1007/s10796-017-9804-9","title":"Big Data Analytics and Business Intelligence in Industry","year":2017,"lang":"en","type":"article","venue":"Information Systems Frontiers","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ontario Institute of Technology","funders":"King Mongkut's Institute of Technology Ladkrabang; Natural Sciences and Engineering Research Council of Canada; National Taipei University of Technology","keywords":"Business intelligence; Big data; Business analytics; Data science; Computer science; Analytics; Data analysis; Knowledge management; Business; Data mining; Business analysis; Business model; Marketing","routes":{"ca_aff":true,"ca_fund":true,"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":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0006482782,0.0001686704,0.0002361802,0.0004573953,0.0003095848,0.00244556,0.001263164,0.0002092503,0.00001134746],"category_scores_gemma":[0.0005659218,0.0001543777,0.00001318047,0.0003931699,0.0001514188,0.01410843,0.0007907523,0.0002426078,0.0001498052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003118836,"about_ca_system_score_gemma":0.0000441175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003877919,"about_ca_topic_score_gemma":0.0001646433,"domain_scores_codex":[0.9987221,0.000005770858,0.0005399722,0.0002101095,0.0002814472,0.0002406424],"domain_scores_gemma":[0.997885,0.00001115659,0.0006001969,0.001201244,0.0002840997,0.00001830522],"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":[0.00005734334,0.00004186863,0.4330922,0.001189411,0.00004741674,0.00001147275,0.0001758987,0.001331116,0.000003569085,0.01414115,0.06797288,0.4819357],"study_design_scores_gemma":[0.0002531865,0.000002039003,0.09497334,0.0003062042,0.00002967653,0.000009345825,0.002052398,0.1767892,0.000004422085,0.0003950402,0.7248058,0.0003793128],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08728851,0.001634848,0.7286333,0.003883427,0.03029547,0.001985829,0.000320967,0.0003962156,0.1455614],"genre_scores_gemma":[0.9981027,0.00009758506,0.0002380263,0.000313579,0.0007825217,0.00001119672,0.0002633245,0.00001004541,0.0001809904],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9108142,"threshold_uncertainty_score":0.9996807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1464499997051727,"score_gpt":0.2997121760576064,"score_spread":0.1532621763524336,"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."}}