{"id":"W4404815214","doi":"10.1016/j.jfoodeng.2024.112415","title":"Effect of model selection approach obtained by machine learning tools on predicting the volume reduction of plant-based dehydrated foods","year":2024,"lang":"en","type":"article","venue":"Journal of Food Engineering","topic":"Machine Learning and ELM","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Selection (genetic algorithm); Volume (thermodynamics); Reduction (mathematics); Machine learning; Artificial intelligence; Computer science; Chemistry; Biochemical engineering; Mathematics; Engineering; Thermodynamics; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001363895,0.00014468,0.0002467188,0.0002515129,0.00006513307,0.00007841695,0.0002778567,0.00006364103,9.520493e-7],"category_scores_gemma":[0.0002361469,0.000100593,0.0001275804,0.0005045304,0.0000104289,0.0002607418,0.0000255284,0.0006099788,2.916832e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005758013,"about_ca_system_score_gemma":0.00005216076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008495875,"about_ca_topic_score_gemma":1.366324e-7,"domain_scores_codex":[0.998819,0.0001350449,0.0004046468,0.0001420308,0.0003328427,0.0001664513],"domain_scores_gemma":[0.9993063,0.0002319259,0.0002342059,0.0001159822,0.00006475113,0.00004681273],"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":[0.00005222675,0.00002417028,0.00007190907,0.0002481146,0.0000833903,0.000001013848,0.0002986123,0.9449331,0.04227047,0.0001270429,0.00008456006,0.01180545],"study_design_scores_gemma":[0.0002886813,0.002307649,0.00003841622,0.0002408999,0.00003612832,0.00008400485,0.000005752343,0.9515759,0.04523605,0.000006247744,0.0001034833,0.00007673842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4008047,0.0003706692,0.5983083,0.00008136394,0.0002194272,0.00007047591,0.000003397474,0.0000876706,0.00005398387],"genre_scores_gemma":[0.9947073,0.000007253924,0.005127884,0.000002988132,0.00009894664,0.000003362611,0.000004710698,0.00001821971,0.00002935029],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5939026,"threshold_uncertainty_score":0.4102064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007553235229878373,"score_gpt":0.2101843629946324,"score_spread":0.202631127764754,"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."}}