{"id":"W2043409061","doi":"10.4018/jbir.2010100101","title":"What is Business Intelligence?","year":2010,"lang":"en","type":"article","venue":"International Journal of Business Intelligence Research","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Business intelligence; Leverage (statistics); Knowledge management; Quality (philosophy); Process (computing); Computer science; Field (mathematics); New business development; Management science; Process management; Business; Business model; Marketing; Engineering; Artificial intelligence","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","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004288062,0.0004894921,0.0005932744,0.003036436,0.0003714775,0.004138933,0.005486062,0.0003626098,0.006981608],"category_scores_gemma":[0.003670301,0.0004120538,0.0002640866,0.004883838,0.001045791,0.01126587,0.001300598,0.00211401,0.002241663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001424281,"about_ca_system_score_gemma":0.0005751636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000895624,"about_ca_topic_score_gemma":0.0002640417,"domain_scores_codex":[0.9926339,0.00005482624,0.001675384,0.0006914737,0.003988463,0.0009558867],"domain_scores_gemma":[0.9690627,0.0005082485,0.0009673087,0.0008277249,0.02852752,0.0001064469],"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":[0.000930424,0.001307291,0.006397914,0.0003584874,0.0003652727,0.0008074071,0.0005016821,0.0009685481,0.01449091,0.07427259,0.0219293,0.8776702],"study_design_scores_gemma":[0.0004471428,0.00006232587,0.01223369,0.002006836,0.0001008461,0.001304626,0.00400305,0.006981958,0.03236119,0.11842,0.8206911,0.001387273],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4321422,0.004427533,0.2850748,0.1113925,0.1355599,0.001769865,0.00007488014,0.0003905297,0.02916778],"genre_scores_gemma":[0.979329,0.004582582,0.001440422,0.001736646,0.01172661,0.00002197507,0.00004193453,0.00009530285,0.001025557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8762829,"threshold_uncertainty_score":0.9998947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1630525501417553,"score_gpt":0.4198032638293555,"score_spread":0.2567507136876002,"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."}}