{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003282462,0.00007184577,0.00006812633,0.00005828187,0.0001142449,0.00005476213,0.0001429719,0.00001430417,0.0008189097],"category_scores_gemma":[0.00003808442,0.00004635494,0.00001711374,0.0002651945,0.00006950547,0.0003179715,0.0001062191,0.00003148215,0.00007048848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004464003,"about_ca_system_score_gemma":0.00001072211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000860878,"about_ca_topic_score_gemma":0.0004719507,"domain_scores_codex":[0.9995176,0.000008927131,0.0001825261,0.0001105003,0.00006553774,0.0001148959],"domain_scores_gemma":[0.9994371,0.00009525326,0.00008993815,0.0001064946,0.0002668431,0.000004364917],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005605123,0.00005226552,0.01865075,0.00006687087,0.00002922101,0.000001462027,0.0004795848,0.000003303792,0.0002477022,0.4854345,0.001857377,0.4931209],"study_design_scores_gemma":[0.0006555336,0.0001326748,0.3376878,0.0001907631,0.0001986366,0.00001305183,0.03733935,0.01383001,0.08568656,0.343784,0.1793017,0.001179918],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03052353,0.000332677,0.8669763,0.0006682445,0.0004261362,0.0005308538,4.777413e-7,0.00006775135,0.100474],"genre_scores_gemma":[0.9977457,0.0001255078,0.001582338,0.0002398658,0.00008490458,0.00001512218,8.610913e-7,0.000006796411,0.0001989181],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9672222,"threshold_uncertainty_score":0.8966488,"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."}}