{"id":"W4400934691","doi":"10.1016/j.compag.2024.109262","title":"Advanced model predictive control strategies for nondestructive monitoring quality of fruit and vegetables during supply chain processes","year":2024,"lang":"en","type":"article","venue":"Computers and Electronics in Agriculture","topic":"Food Supply Chain Traceability","field":"Agricultural and Biological Sciences","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"National Key Research and Development Program of China Stem Cell and Translational Research","keywords":"Model predictive control; Quality (philosophy); Supply chain; Control (management); Monitoring and control; Engineering; Reliability engineering; Computer science; Business; Control engineering; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002087414,0.0001905673,0.0003010003,0.00001735492,0.0001152557,0.0001083201,0.0001236578,0.000121541,6.564653e-7],"category_scores_gemma":[0.00003392764,0.00008063159,0.00005013632,0.000262499,0.00008055207,0.0003130359,0.00004357508,0.0002113366,4.048834e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006452459,"about_ca_system_score_gemma":0.00004532268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003973965,"about_ca_topic_score_gemma":0.0004101959,"domain_scores_codex":[0.9988146,0.00004425044,0.0002564572,0.0004343069,0.0001287192,0.0003216568],"domain_scores_gemma":[0.9993247,0.0004009791,0.00006610725,0.00003886849,0.0001131373,0.00005623099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0009253885,0.0002925074,0.03212444,0.003397836,0.0002509442,0.000005693099,0.005573757,0.05294548,0.8595609,0.01705026,0.0000757634,0.02779701],"study_design_scores_gemma":[0.0035793,0.00323451,0.7153212,0.001685533,0.0001370579,0.00005018275,0.01475779,0.09836513,0.0439502,0.1168259,0.0003973893,0.001695715],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861718,0.01186865,0.0008120373,0.0003043753,0.00007245169,0.0005526351,0.000137738,0.00005948192,0.0000208557],"genre_scores_gemma":[0.9984671,0.0005994258,0.0007036501,0.000007635183,0.0001054175,0.00008059634,0.00001963065,0.000001730245,0.00001482755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8156107,"threshold_uncertainty_score":0.3288061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01115438799503775,"score_gpt":0.2403351141010741,"score_spread":0.2291807261060363,"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."}}