{"id":"W3111674244","doi":"10.1109/smc42975.2020.9282887","title":"Machine Learning Tools for the Prediction of Fresh Produce Procurement Price","year":2020,"lang":"en","type":"article","venue":"","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Procurement; Computer science; Machine learning; Artificial intelligence; Business; Marketing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001201493,0.0007547188,0.0005787886,0.001845496,0.0002955373,0.0007833432,0.0006356754,0.0006110563,0.001058302],"category_scores_gemma":[0.004643765,0.0002449497,0.0005745915,0.001503412,0.0001704658,0.0006866329,0.0003815845,0.001183265,0.0003873105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007180647,"about_ca_system_score_gemma":0.0009351185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01464284,"about_ca_topic_score_gemma":0.01182592,"domain_scores_codex":[0.9996247,0.0001239526,0.00004512244,0.00007675242,0.00009234212,0.000036992],"domain_scores_gemma":[0.9977067,0.001720601,0.0001830365,0.00008586875,0.0002629369,0.00004085436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006748219,0.0002103658,0.0115977,0.00006222504,0.00009215554,0.00006275041,0.00003461166,0.8010395,0.0009134573,0.00159403,0.002500632,0.1818251],"study_design_scores_gemma":[0.000001475753,0.000008119522,0.0006414703,0.000003677907,0.000003241866,0.000002704083,0.000005343721,0.9986162,0.0001409555,0.0004553046,0.0001193085,0.000002121464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2965843,0.002491431,0.6876557,0.001440936,0.000161214,0.0001606964,0.002203349,0.004482532,0.00481993],"genre_scores_gemma":[0.8848513,0.0007648986,0.1107357,0.00009560662,0.0000824407,0.0001436625,0.0020191,0.0000346881,0.001272393],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01464284,"threshold_uncertainty_score":0.0291152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2899449303835664,"score_gpt":0.3822847858423819,"score_spread":0.09233985545881551,"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."}}