{"id":"W2563642040","doi":"","title":"Generating Valuable Insights through Data Analytics: A Moderating Effects Model","year":2016,"lang":"en","type":"article","venue":"International Conference on Information Systems","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Data science; Analytics; Data modeling; Database","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":[0.03308339,0.002575838,0.001452817,0.002176047,0.001690174,0.003255099,0.002277748,0.002796927,0.01223603],"category_scores_gemma":[0.1518146,0.001165286,0.001952517,0.002301841,0.002567089,0.006913126,0.006121974,0.004609441,0.001112995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009673139,"about_ca_system_score_gemma":0.002470828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002872292,"about_ca_topic_score_gemma":0.002509005,"domain_scores_codex":[0.9718887,0.02182635,0.0006730682,0.003120743,0.00161443,0.0008768084],"domain_scores_gemma":[0.6877825,0.2856001,0.006840535,0.01098234,0.005933772,0.00286084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.02108381,0.01095799,0.4252673,0.003784806,0.01192777,0.002017611,0.02590919,0.03817156,0.02770479,0.228899,0.008450401,0.1958257],"study_design_scores_gemma":[0.005824903,0.008746808,0.1255707,0.0009881095,0.02447002,0.001220187,0.005472272,0.3876079,0.02011606,0.4012539,0.01807233,0.0006568439],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6830451,0.001397967,0.2830887,0.006793333,0.0004370714,0.002160721,0.001811073,0.0007176367,0.02054833],"genre_scores_gemma":[0.9494917,0.00026688,0.04583789,0.000303797,0.00009148935,0.001165922,0.0002645518,0.00009968384,0.00247813],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03308339,"threshold_uncertainty_score":0.1749638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2045811838272737,"score_gpt":0.3328413930317528,"score_spread":0.1282602092044791,"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."}}