{"id":"W24693550","doi":"","title":"Special Considerations for Business Intelligence Projects","year":2009,"lang":"en","type":"article","venue":"˜The œopen source business resource","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Business intelligence; Business; Computer science; Knowledge management","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":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000971936,0.0006467922,0.0006409296,0.0004007614,0.001759894,0.003827191,0.002548514,0.0002367598,0.001015211],"category_scores_gemma":[0.001062678,0.0004936313,0.0001583127,0.003220919,0.0003912902,0.002375744,0.000963365,0.0002791137,0.0006096489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007041707,"about_ca_system_score_gemma":0.000207445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008586938,"about_ca_topic_score_gemma":0.0006758668,"domain_scores_codex":[0.9964671,0.00004184214,0.0008685234,0.001045497,0.0006369171,0.0009400883],"domain_scores_gemma":[0.9958032,0.0004200778,0.0006167133,0.001328299,0.00178441,0.00004723913],"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":[0.000936725,0.0009146871,0.001004467,0.0004557482,0.0001018785,0.00004248694,0.0006417964,0.007219648,0.0005826584,0.08200987,0.5931018,0.3129883],"study_design_scores_gemma":[0.0005180648,0.00001826093,0.00865541,0.0001755907,0.0001288271,0.00005341932,0.0005734068,0.003819757,0.00009012166,0.01350015,0.9716789,0.0007881562],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02805058,0.0008973089,0.474712,0.07901008,0.007046452,0.01645355,0.0001708706,0.00204415,0.391615],"genre_scores_gemma":[0.9021177,0.00004834994,0.002884617,0.03335183,0.04443152,0.0006059889,0.0005265929,0.0002668648,0.01576654],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8740671,"threshold_uncertainty_score":0.999898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1013525123944212,"score_gpt":0.3054616350340638,"score_spread":0.2041091226396425,"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."}}