{"id":"W2484021251","doi":"10.1145/2963143","title":"The Six Pillars for Building Big Data Analytics Ecosystems","year":2016,"lang":"en","type":"review","venue":"ACM Computing Surveys","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada); Queen's University","funders":"","keywords":"Analytics; Computer science; Big data; Data science; Process (computing); Data analysis; Ecosystem; Web analytics; World Wide Web; Data mining; Ecology; The Internet; Web 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01882226,0.002172177,0.001478776,0.01081701,0.005125003,0.0223246,0.004510709,0.00955498,0.004550403],"category_scores_gemma":[0.01372781,0.001534467,0.001636844,0.01355764,0.01302134,0.03550628,0.01507031,0.01280034,0.004785149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005586475,"about_ca_system_score_gemma":0.01043263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002930172,"about_ca_topic_score_gemma":0.002556492,"domain_scores_codex":[0.9858862,0.005386354,0.001589539,0.001482646,0.004617517,0.001037754],"domain_scores_gemma":[0.983169,0.007327021,0.001350679,0.002355803,0.00408028,0.001717324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002563157,0.0000969003,0.001357848,0.003272836,0.00005796786,0.0001952842,0.001399774,0.0007038969,0.0004732727,0.768925,0.03873629,0.1847555],"study_design_scores_gemma":[0.0000122488,0.00004094338,0.0008179115,0.004380394,0.00002833619,0.0004737175,0.00196667,0.0009258974,0.0003623311,0.322701,0.6682267,0.00006380562],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.005918182,0.4517942,0.1851151,0.2306546,0.00442579,0.001697639,0.0007207761,0.001338815,0.1183349],"genre_scores_gemma":[0.07189561,0.4946943,0.3527645,0.05088397,0.005308023,0.003381034,0.001575558,0.0004976742,0.01899924],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.0223246,"threshold_uncertainty_score":0.09954286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3573498816909544,"score_gpt":0.3903184238851551,"score_spread":0.03296854219420065,"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."}}