{"id":"W2945006129","doi":"10.1109/icbda.2019.8713257","title":"Big Data Analytics for Higher Education in The Cloud Era","year":2019,"lang":"en","type":"article","venue":"","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Big data; Cloud computing; Analytics; Data science; Computer science; Learning analytics; Business intelligence; Knowledge management; Face (sociological concept); Data management; Data analysis; Higher education; Business; Political science; Data mining","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":[],"consensus_categories":[],"category_scores_codex":[0.0003405891,0.00008137607,0.00008227792,0.00009873428,0.00004254184,0.0002664332,0.0008619418,0.00003761496,0.000760727],"category_scores_gemma":[0.00003901456,0.000050958,0.00001874179,0.0004128918,0.00001545794,0.0008470758,0.0001974621,0.00006735346,0.0006263187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007254017,"about_ca_system_score_gemma":0.00004545402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006092226,"about_ca_topic_score_gemma":0.0002556387,"domain_scores_codex":[0.9993579,0.000003284068,0.0001477039,0.0002240587,0.0001262286,0.0001408585],"domain_scores_gemma":[0.999051,0.00005122853,0.0000648581,0.0007497008,0.00008058902,0.000002632737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003016922,0.0002517855,0.047721,0.0002512671,0.00001266311,3.937924e-7,0.00001321351,0.000025741,0.00006874989,0.3095841,0.503397,0.1386439],"study_design_scores_gemma":[0.000101466,0.000001985268,0.02547374,0.00001873777,0.00001949786,2.783995e-7,0.0001189966,0.003368349,0.00000646557,0.004516738,0.9662745,0.00009927648],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.367649,0.0006618278,0.01482486,0.0511643,0.02603693,0.003281494,0.00009078215,0.0002324219,0.5360584],"genre_scores_gemma":[0.9726387,0.00001121559,0.0002693633,0.009809993,0.004126342,0.00001457025,0.000766871,0.00001246353,0.01235052],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6049896,"threshold_uncertainty_score":0.8329427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2050269588930196,"score_gpt":0.3397960081166699,"score_spread":0.1347690492236504,"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."}}