{"id":"W4311514101","doi":"10.5267/j.ijdns.2022.12.009","title":"The effects of big data, artificial intelligence, and business intelligence on e-learning and business performance: Evidence from Jordanian telecommunication firms","year":2022,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Organizational and Employee Performance","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Applied Science Private University","keywords":"Business intelligence; Big data; Knowledge management; Computer science; Business activity monitoring; Business analytics; Competitive intelligence; Business process; Data warehouse; Intelligence cycle; Data science; Artificial intelligence; Business process modeling; Business; Business analysis; Database; Business model; Marketing; Data mining","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002031535,0.0001107723,0.0001456543,0.0001517537,0.000881183,0.0004204009,0.005064977,0.00001859541,0.000003778999],"category_scores_gemma":[0.0008928391,0.00008123087,0.000008512567,0.001191923,0.0004850571,0.002442664,0.004889409,0.0003019104,9.831762e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003500463,"about_ca_system_score_gemma":0.000278555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005138876,"about_ca_topic_score_gemma":0.00001781323,"domain_scores_codex":[0.9980409,0.00009630087,0.0004493897,0.0003612113,0.0008725283,0.0001797336],"domain_scores_gemma":[0.9971499,0.001130374,0.000455296,0.0005930449,0.0005972952,0.00007407798],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001014438,0.0000571139,0.019372,0.00002115666,0.00002928044,0.000007296937,0.0004965362,0.006242543,0.0004108492,0.003246693,0.0001300579,0.9698851],"study_design_scores_gemma":[0.0002143021,0.0006563379,0.2042323,0.001070661,0.0000422792,0.0004046392,0.0003647426,0.7671402,0.001941717,0.01293815,0.01057183,0.0004228205],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7871696,0.00650015,0.1993221,0.003520391,0.003231326,0.000159996,0.00003318316,0.00001757994,0.00004564798],"genre_scores_gemma":[0.9751332,0.01779768,0.006590494,0.00009761065,0.0003495054,0.000001675836,0.00001701614,0.000004915389,0.000007897521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9694622,"threshold_uncertainty_score":0.9412072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05402003640020429,"score_gpt":0.2970761722188336,"score_spread":0.2430561358186293,"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."}}