{"id":"W4301594995","doi":"10.1007/s11947-022-02917-x","title":"Research on the Vegetable Shrinkage During Drying and Characterization and Control Based on LF-NMR","year":2022,"lang":"en","type":"article","venue":"Food and Bioprocess Technology","topic":"Food Drying and Modeling","field":"Agricultural and Biological Sciences","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Shrinkage; Water content; Chemistry; Moisture; Volume (thermodynamics); Food science; Materials science; Composite material; Thermodynamics","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":[0.0003806546,0.00009291529,0.0001109854,0.00007157445,0.001223207,0.00006359169,0.000137391,0.00008361566,0.00001557295],"category_scores_gemma":[0.0000351127,0.00003681353,0.00001161255,0.0004019282,0.0001250912,0.00003707335,0.0001334072,0.0003391921,8.808901e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001131418,"about_ca_system_score_gemma":0.000005130822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001694049,"about_ca_topic_score_gemma":0.00001609675,"domain_scores_codex":[0.999123,0.00005408864,0.00009665328,0.0003120048,0.0001659432,0.0002483219],"domain_scores_gemma":[0.9997232,0.0001143182,0.00003899795,0.00005586023,0.00003469863,0.00003290259],"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":[0.0001424758,0.00007469358,0.003843402,0.00003570136,0.0000105005,0.000004168041,0.00006742825,0.00003390381,0.9567927,0.001977895,0.000003944664,0.03701325],"study_design_scores_gemma":[0.004977501,0.02629188,0.1917691,0.0005737653,0.00007741028,0.0002017004,0.0136579,0.04266713,0.6859167,0.01050563,0.02146331,0.001897992],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907565,0.0002788535,0.000005381882,0.008551405,0.00002294675,0.0001816244,0.00002673029,0.000090282,0.00008631363],"genre_scores_gemma":[0.9994686,0.00005081435,0.000005869219,0.0002789317,0.00003975222,0.00008639293,0.00001013326,0.000001504633,0.00005798275],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2708759,"threshold_uncertainty_score":0.9408045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02842845168490362,"score_gpt":0.2417260250335138,"score_spread":0.2132975733486102,"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."}}