{"id":"W1993708925","doi":"10.1108/02635570810876750","title":"A knowledge management approach to data mining process for business intelligence","year":2008,"lang":"en","type":"article","venue":"Industrial Management & Data Systems","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":152,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Knowledge management; Tacit knowledge; Computer science; Knowledge sharing; Business intelligence; Business process discovery; Artifact-centric business process model; Process mining; Business process; Context (archaeology); Business process modeling; Process (computing); Business process management; Knowledge extraction; Explicit knowledge; Process management; Business; Data mining; Work in process","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","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.002086019,0.0007081716,0.0007608751,0.001007755,0.000724807,0.001124266,0.009379842,0.0002483889,0.00005198357],"category_scores_gemma":[0.0003558475,0.0006685667,0.00006358996,0.003829163,0.0001562296,0.005075207,0.008274798,0.0002552686,0.0006689696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008950724,"about_ca_system_score_gemma":0.00007395991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004885027,"about_ca_topic_score_gemma":0.0000356719,"domain_scores_codex":[0.9941885,0.00003943019,0.001275656,0.002497345,0.0009369082,0.001062197],"domain_scores_gemma":[0.9934031,0.0001005713,0.000552511,0.005343333,0.000515801,0.00008472121],"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":[0.0005333967,0.001384424,0.001286717,0.006705756,0.000693056,0.0001035052,0.0001646584,0.001909462,0.000007240032,0.03219992,0.8306434,0.1243685],"study_design_scores_gemma":[0.0009564351,0.00001650061,0.0003457105,0.0008459577,0.0004357465,0.00002500624,0.002943609,0.07102348,0.000005045223,0.00008675293,0.9223065,0.001009249],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004824106,0.001129717,0.6627867,0.00107107,0.01483954,0.01781423,0.002584073,0.001342492,0.2936081],"genre_scores_gemma":[0.9312974,0.000316886,0.008619581,0.001034379,0.01727207,0.002320351,0.03041977,0.0003481488,0.008371439],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9264733,"threshold_uncertainty_score":0.9999127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5306810694722821,"score_gpt":0.373202065390516,"score_spread":0.1574790040817661,"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."}}