{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.01011808,0.0006731991,0.001432911,0.0003086958,0.001551444,0.001320285,0.007343189,0.0003018377,0.00001637356],"category_scores_gemma":[0.006246496,0.0003923718,0.0003514137,0.001082091,0.000121488,0.0005793693,0.007579295,0.0003334454,0.0003230401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007415335,"about_ca_system_score_gemma":0.0001674317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003243552,"about_ca_topic_score_gemma":0.0004398224,"domain_scores_codex":[0.9961441,0.0002192976,0.001252363,0.001106816,0.000443102,0.0008342882],"domain_scores_gemma":[0.9889444,0.004846165,0.001542725,0.00418262,0.0004597056,0.00002442902],"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":[0.000001576657,0.00001460595,0.00009455484,0.007757655,0.0001694413,0.000002837697,0.00000134473,0.000002776436,1.271366e-7,0.001177155,0.02159307,0.9691849],"study_design_scores_gemma":[0.00009811238,0.00000358391,0.00001573662,0.00988019,0.0004053025,0.000008045328,0.000005196261,0.003381591,1.44814e-7,0.0004146453,0.9852066,0.0005808669],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00000750104,0.9060104,0.08392935,0.0002021673,0.007935904,0.001015259,0.0003885649,0.0002024509,0.0003083614],"genre_scores_gemma":[0.000317487,0.9829386,0.0005059442,0.0001070488,0.01356502,0.00002342178,0.00207462,0.0001674335,0.0003004461],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.968604,"threshold_uncertainty_score":0.9998528,"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."}}