{"id":"W2038634726","doi":"10.1080/07373931003788049","title":"Control of Microwave Drying Process Through Aroma Monitoring","year":2010,"lang":"en","type":"article","venue":"Drying Technology","topic":"Food Drying and Modeling","field":"Agricultural and Biological Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Aroma; Microwave; Fuzzy logic; Process engineering; Process (computing); Fuzzy control system; Computer science; Engineering; Chemistry; Artificial intelligence; Food science; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000238102,0.0002586118,0.0002152636,0.0001521158,0.000129127,0.0002535397,0.0003104681,0.000143462,0.0003804035],"category_scores_gemma":[0.0003466701,0.0001236227,0.0001366515,0.0001157523,0.0001760183,0.0001726183,0.0001135622,0.0001479547,0.0001041892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000142586,"about_ca_system_score_gemma":0.0001182768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005573852,"about_ca_topic_score_gemma":0.0005878032,"domain_scores_codex":[0.9998916,0.00001691323,0.000005852459,0.00003291109,0.00004124249,0.00001140111],"domain_scores_gemma":[0.99991,0.00003162426,0.00002076212,0.000008563385,0.0000241914,0.000004903517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001648915,0.00006075063,0.0008285717,0.0001153622,0.00000949267,0.00003584024,0.0000498784,0.01296007,0.9373525,0.0003611736,0.0001291741,0.04793219],"study_design_scores_gemma":[0.00006198305,0.0005568674,0.005081983,0.000009920854,0.00003655581,0.0001262369,0.00002152242,0.3464091,0.6446522,0.0003283475,0.002683811,0.000031296],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6216118,0.0006335253,0.373644,0.00007578903,0.00004590458,0.0001089153,0.00005963267,0.0008879047,0.002932599],"genre_scores_gemma":[0.9731331,0.0002001832,0.02571218,0.00001495673,0.000008079061,0.00003503282,0.00002138827,0.00001514849,0.0008598321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005573852,"threshold_uncertainty_score":0.001272559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01568120231096532,"score_gpt":0.2447289813999526,"score_spread":0.2290477790889872,"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."}}