{"id":"W1493909250","doi":"10.1006/bioe.2002.0123","title":"AE—Automation and Emerging Technologies","year":2002,"lang":"en","type":"article","venue":"Biosystems Engineering","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":74,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Airflow; Artificial neural network; Approximation error; Backpropagation; Air temperature; Volumetric flow rate; Water content; Energy consumption; Moisture; Process engineering; Environmental science; Biological system; Simulation; Materials science; Mathematics; Meteorology; Engineering; Computer science; Statistics; Machine learning; Composite material; Mechanical engineering; Geotechnical engineering; Mechanics","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":[0.005540212,0.00119464,0.001053064,0.002724077,0.000910138,0.007049469,0.002494056,0.002045976,0.01031629],"category_scores_gemma":[0.007603718,0.0007014521,0.0008487263,0.002743092,0.003139253,0.01165101,0.003205331,0.004616526,0.007817449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0011755,"about_ca_system_score_gemma":0.001285011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005935545,"about_ca_topic_score_gemma":0.0003385352,"domain_scores_codex":[0.9942448,0.001568767,0.000420373,0.0008848297,0.002559931,0.0003212688],"domain_scores_gemma":[0.9912441,0.003291178,0.000348442,0.002123063,0.002595984,0.0003972075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000134222,0.0001345929,0.001022913,0.0005976759,0.00004708309,0.0001265059,0.0001887117,0.002050398,0.0111876,0.3641853,0.01320719,0.6071179],"study_design_scores_gemma":[0.00005230008,0.0003229416,0.001833059,0.0004810853,0.00005137354,0.001832075,0.0002774075,0.03581783,0.03099711,0.444681,0.4835649,0.0000889444],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008093971,0.02914019,0.9050019,0.006350838,0.001847153,0.0001520999,0.0001702631,0.002059549,0.04718411],"genre_scores_gemma":[0.1381803,0.03361726,0.7800809,0.0026453,0.004182071,0.0002441043,0.0007861352,0.0004845087,0.03977943],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01031629,"threshold_uncertainty_score":0.03451139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009634405340607806,"score_gpt":0.2024086528939183,"score_spread":0.1927742475533105,"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."}}