{"id":"W2075020675","doi":"10.1145/1923947.1923986","title":"Introduction to IBM Cognos 8 business intelligence","year":2010,"lang":"en","type":"article","venue":"","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada)","funders":"","keywords":"IBM; Computer science; Business intelligence; Knowledge management","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":[0.00103927,0.001092544,0.0005041994,0.002718262,0.001161058,0.007233123,0.001177266,0.001457144,0.07578698],"category_scores_gemma":[0.002644745,0.0007253852,0.0004485524,0.003636757,0.0008001403,0.006326376,0.001969287,0.003292579,0.08033437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001517733,"about_ca_system_score_gemma":0.002002744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004035125,"about_ca_topic_score_gemma":0.004977433,"domain_scores_codex":[0.9985484,0.000165329,0.00007181944,0.0002280548,0.0008458368,0.0001404792],"domain_scores_gemma":[0.9988456,0.0001651646,0.00004357112,0.0001567287,0.0005882836,0.000200617],"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":[0.0000538454,0.00005245051,0.0002458874,0.0001512811,0.000007664782,0.00008173274,0.0001419221,0.0002935388,0.0008784352,0.06956346,0.6855997,0.2429301],"study_design_scores_gemma":[0.000004243578,0.000008584181,0.0001574194,0.00004907513,0.000002421949,0.00007641395,0.00003050941,0.0003360994,0.0002288147,0.009986795,0.9891106,0.000008906527],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001847223,0.01268686,0.04609377,0.01414701,0.006307255,0.0002392692,0.002299547,0.0125629,0.903816],"genre_scores_gemma":[0.02812453,0.02245804,0.1202246,0.008663118,0.005781449,0.0003370299,0.007036495,0.004775638,0.8025991],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.07578698,"threshold_uncertainty_score":0.2535327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03665875547316659,"score_gpt":0.2751215333345268,"score_spread":0.2384627778613602,"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."}}