{"id":"W4206621223","doi":"10.1080/08874417.2021.2010150","title":"Understanding Data Analytics Recommendation Execution: The Role of Recommendation Quality","year":2022,"lang":"en","type":"article","venue":"Journal of Computer Information Systems","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Analytics; Quality (philosophy); Data quality; Recommender system; Concordance; Data science; Sample (material); Perception; Knowledge management; World Wide Web; Psychology; Business; Medicine; Marketing","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":[0.01024,0.0003123953,0.0002897467,0.001582316,0.0007467353,0.00588111,0.0006037686,0.001218637,0.001701859],"category_scores_gemma":[0.0621924,0.000317978,0.0004592433,0.001278494,0.001958166,0.005327941,0.001538274,0.001535551,0.0002290677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001832744,"about_ca_system_score_gemma":0.002094975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01150159,"about_ca_topic_score_gemma":0.008942847,"domain_scores_codex":[0.9942478,0.002874553,0.0004644459,0.0006552872,0.001323176,0.0004346849],"domain_scores_gemma":[0.9171533,0.05799433,0.01321256,0.003607978,0.0056134,0.002418416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002011166,0.0004921071,0.9209187,0.0001504357,0.0001424347,0.0001023977,0.02113397,0.002162545,0.001665304,0.008155502,0.0004394074,0.044436],"study_design_scores_gemma":[0.00006250013,0.0005374738,0.9093483,0.0001657417,0.0001477856,0.0001409471,0.03219188,0.03306375,0.001816745,0.01856541,0.00384956,0.0001098474],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9786128,0.0002206848,0.01211485,0.001831656,0.000009682861,0.00007881767,0.00010603,0.00004131577,0.006984215],"genre_scores_gemma":[0.9971922,0.00004505576,0.002517966,0.00006027431,0.000003659451,0.00001062933,0.00004203725,0.000004847444,0.0001233806],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01150159,"threshold_uncertainty_score":0.05415493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3274491641562817,"score_gpt":0.3363506713615658,"score_spread":0.008901507205284098,"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."}}