{"id":"W3001872177","doi":"10.1002/leg3.31","title":"Kinetics of a thin‐layer microwave‐assisted infrared drying of lentil seeds","year":2020,"lang":"en","type":"article","venue":"Legume Science","topic":"Food Drying and Modeling","field":"Agricultural and Biological Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Microwave; Coefficient of determination; Thin layer; Materials science; Infrared; Response surface methodology; Microwave power; Particle size; Raw material; Analytical Chemistry (journal); Mathematics; Pulp and paper industry; Chemistry; Layer (electronics); Composite material; Chromatography; Statistics; Optics; Computer science; Physics; Organic chemistry","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":[0.000186947,0.0001835419,0.0001474074,0.0001188315,0.00007045615,0.0001631852,0.0001579968,0.0001025876,0.0004206755],"category_scores_gemma":[0.0002309964,0.00009073505,0.0001925625,0.00009858235,0.00007407631,0.000177951,0.00006216593,0.0001791412,0.0001290829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000157831,"about_ca_system_score_gemma":0.0001025164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00119491,"about_ca_topic_score_gemma":0.00101199,"domain_scores_codex":[0.9999509,0.00000620457,0.000003107187,0.00001082401,0.00002306496,0.000006031469],"domain_scores_gemma":[0.9999183,0.00002833234,0.0000247508,0.000007815139,0.00001584459,0.000004900081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005414612,0.00002063982,0.0008239886,0.00005881426,0.000009477667,0.00004292983,0.0000218987,0.003818837,0.9922869,0.0001195375,0.00003894004,0.002703915],"study_design_scores_gemma":[0.000005345253,0.0001286006,0.004047768,0.000003980196,0.00001257434,0.00005486092,0.0000133114,0.0646267,0.9304858,0.00004578873,0.0005653865,0.000009898476],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9863787,0.0005842962,0.01212844,0.00002174652,0.000008555183,0.00001708315,0.0001049326,0.00005518663,0.0007010966],"genre_scores_gemma":[0.9934325,0.0004452212,0.004927161,0.000009433912,0.000002459561,0.00001183024,0.0001076497,0.00001378276,0.001049929],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00119491,"threshold_uncertainty_score":0.002375901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0529055014043297,"score_gpt":0.24176780456382,"score_spread":0.1888623031594903,"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."}}