{"id":"W1993753066","doi":"10.1109/3pgcic.2011.40","title":"The Design and Implementation of a Business Intelligence Recommender","year":2011,"lang":"en","type":"article","venue":"","topic":"Competitive and Knowledge Intelligence","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Recommender system; Business intelligence; World Wide Web; Business information; Crawling; The Internet; Population; Information retrieval; 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":[0.001795256,0.000398011,0.0008098601,0.000542513,0.0006664561,0.001764927,0.003047015,0.002454945,0.005049195],"category_scores_gemma":[0.002894021,0.0007297255,0.0006502154,0.0004708841,0.0002879282,0.001342299,0.0008423998,0.001172632,0.00375816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000513447,"about_ca_system_score_gemma":0.001236529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004816291,"about_ca_topic_score_gemma":0.004403477,"domain_scores_codex":[0.9987838,0.0002289271,0.0001577856,0.0002698604,0.0004280071,0.000131604],"domain_scores_gemma":[0.9985985,0.0002085112,0.00006610039,0.0002599804,0.0007062539,0.0001605991],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000984319,0.001424619,0.009785044,0.001085165,0.0004257594,0.001906006,0.001380484,0.06448157,0.1887974,0.04442337,0.0162169,0.6690894],"study_design_scores_gemma":[0.0003370878,0.00148458,0.003220491,0.0001247401,0.0003860947,0.0014846,0.0003591306,0.7335668,0.09392251,0.004565226,0.1603644,0.0001842636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02410499,0.0002320987,0.9575663,0.0004292467,0.0001436027,0.001380764,0.0001308596,0.00720394,0.00880823],"genre_scores_gemma":[0.1122181,0.0002498302,0.8718232,0.0002246283,0.00003650298,0.000662006,0.0003822418,0.0001894372,0.01421394],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005049195,"threshold_uncertainty_score":0.01689124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08178126780762654,"score_gpt":0.2821361540572689,"score_spread":0.2003548862496424,"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."}}