{"id":"W2993977893","doi":"10.1088/1757-899x/688/5/055026","title":"Analysis of the Whole Industry Chain of Jiang Xiaobai Sorghum Wine","year":2019,"lang":"en","type":"article","venue":"IOP Conference Series Materials Science and Engineering","topic":"Service and Product Innovation","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Product (mathematics); Business; Upgrade; Chain (unit); Order (exchange); Wine; New product development; Product marketing; Marketing; Process management; Manufacturing engineering; Industrial organization; Computer science; Engineering; Mathematics; Marketing strategy","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":[0.0003311681,0.0002441022,0.0001933496,0.003328919,0.0007945491,0.00112717,0.0002738731,0.0003010038,0.00668457],"category_scores_gemma":[0.0006644689,0.0002494142,0.0006685096,0.002416167,0.0002670741,0.0009836316,0.0003833998,0.0002300237,0.0004840626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001338341,"about_ca_system_score_gemma":0.001045439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04276477,"about_ca_topic_score_gemma":0.02416596,"domain_scores_codex":[0.9998181,0.00003147141,0.000009544819,0.00003574977,0.0000550815,0.00005006043],"domain_scores_gemma":[0.9995794,0.0001195945,0.00005625706,0.0000208139,0.0001729173,0.00005109754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005452784,0.000293917,0.6057385,0.0003474711,0.0003099394,0.003564375,0.003603761,0.2085963,0.02101227,0.0430801,0.001894307,0.1110139],"study_design_scores_gemma":[0.00002316245,0.0002519405,0.2193591,0.00007188512,0.0001581935,0.0002678853,0.005852303,0.7535998,0.004655376,0.01051779,0.005188304,0.00005427401],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9778973,0.0001365083,0.01453316,0.00008563668,0.000006917074,0.00004733341,0.0002530326,0.00003620232,0.007003919],"genre_scores_gemma":[0.9941686,0.00009991824,0.002348972,0.0000070586,0.000001746263,0.00001802006,0.0002524529,0.000006694034,0.003096515],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04276477,"threshold_uncertainty_score":0.08503175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01272350551865908,"score_gpt":0.1982722757942645,"score_spread":0.1855487702756054,"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."}}