{"id":"W4312589500","doi":"10.4018/jgim.315646","title":"The Impact of Quality of Big Data Marketing Analytics (BDMA) on the Market and Financial Performance","year":2022,"lang":"en","type":"article","venue":"Journal of Global Information Management","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Concordia University; Thompson Rivers University","funders":"","keywords":"Software deployment; Marketing; Big data; Business; Quality (philosophy); Perspective (graphical); Information technology; Sample (material); Computer science; Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005294595,0.0001047114,0.0001760537,0.0001135914,0.0003308631,0.0001678128,0.0009453049,0.00001722294,0.0001147903],"category_scores_gemma":[0.0004616954,0.00005897255,0.00007917112,0.0006605606,0.000080826,0.001519066,0.001025851,0.0001484976,0.000003022863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007858653,"about_ca_system_score_gemma":0.0000415532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008916311,"about_ca_topic_score_gemma":0.000008403374,"domain_scores_codex":[0.9982169,0.00005095507,0.0008568388,0.00006550202,0.0006677039,0.0001421119],"domain_scores_gemma":[0.9974859,0.0001267057,0.001701177,0.0004055069,0.0002716515,0.000009016509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003032294,0.0002050233,0.07947733,0.001015656,0.0003828401,0.000003179887,0.00007248708,0.009900569,0.000007089079,0.04346849,0.2827212,0.5797138],"study_design_scores_gemma":[0.0004596805,0.00007268918,0.8264765,0.0001163798,0.00009033922,0.000008258031,0.001325072,0.0294365,0.000003767054,0.001068547,0.140805,0.0001372893],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9381536,0.0002065168,0.003782708,0.002749744,0.001145704,0.000481083,0.0002339983,0.00001203466,0.05323462],"genre_scores_gemma":[0.9990718,0.0002495714,0.00007398496,0.0004036734,0.0001470974,0.000001913365,0.00001945781,0.000002507379,0.0000299648],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7469992,"threshold_uncertainty_score":0.2544765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1019579772684758,"score_gpt":0.3254092825534987,"score_spread":0.2234513052850229,"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."}}