{"id":"W3046653697","doi":"10.4018/jgim.20210701.oa1","title":"A Rule-Based Quality Analytics System for the Global Wine Industry","year":2020,"lang":"en","type":"article","venue":"Journal of Global Information Management","topic":"Fermentation and Sensory Analysis","field":"Agricultural and Biological Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Wine; Quality (philosophy); Production (economics); Analytics; China; Business; Environmental economics; Association rule learning; Computer science; Consumption (sociology); Data science; Data mining; Economics; Geography; Microeconomics","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":[0.001153498,0.0007667716,0.001008519,0.001323988,0.000564296,0.00181952,0.00149268,0.0007862261,0.00339902],"category_scores_gemma":[0.002574964,0.0003894048,0.0009035212,0.0008121287,0.0002825185,0.001573983,0.0008651394,0.0009118007,0.001756566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00055193,"about_ca_system_score_gemma":0.0008999942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005388985,"about_ca_topic_score_gemma":0.004159164,"domain_scores_codex":[0.99929,0.0000642937,0.0001197395,0.0002741815,0.0002083487,0.00004340789],"domain_scores_gemma":[0.9988637,0.0002988199,0.0001241383,0.0002127587,0.0004250008,0.00007557275],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001580545,0.001525349,0.02947361,0.0007909022,0.0006147951,0.002680561,0.0007089676,0.105546,0.09110373,0.0064301,0.020536,0.7390094],"study_design_scores_gemma":[0.0001200382,0.0003187396,0.00598191,0.00007709012,0.0001879696,0.0005048551,0.0001183321,0.9489974,0.02627577,0.004076106,0.0132732,0.00006850171],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1097175,0.0009590348,0.8009732,0.001034393,0.000293729,0.0009095853,0.004869229,0.07366888,0.007574383],"genre_scores_gemma":[0.6369016,0.0005742945,0.3503304,0.0005471624,0.00008510071,0.0004470795,0.005369612,0.0004009579,0.005343832],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005388985,"threshold_uncertainty_score":0.01137084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05137739246582527,"score_gpt":0.2900499302621876,"score_spread":0.2386725377963623,"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."}}