{"id":"W2372875118","doi":"","title":"Application of Ultrasonic Extraction Technology Advances in Agricultural Science","year":2014,"lang":"en","type":"article","venue":"Academic Periodical of Farm Products Processing","topic":"Agricultural Engineering and Mechanization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Ultrasonic sensor; Extraction (chemistry); Raw material; Agriculture; Computer science; Process engineering; Pulp and paper industry; Chromatography; Chemistry; Engineering; Medicine; Organic chemistry; Geography","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":[0.0002554793,0.0001090678,0.0001770497,0.0001972129,0.00005580275,0.000009403071,0.0002097943,0.0001421208,6.134205e-7],"category_scores_gemma":[0.0003327322,0.00008396896,0.00001245295,0.001643939,0.0002085202,0.0004546233,0.00001762777,0.0003251479,0.000001225652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000691578,"about_ca_system_score_gemma":0.00004168001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002287898,"about_ca_topic_score_gemma":9.340038e-7,"domain_scores_codex":[0.9990393,0.000006377467,0.0003262275,0.0002149252,0.0002118074,0.0002013795],"domain_scores_gemma":[0.9995946,0.00001330882,0.0001070527,0.00009211434,0.0001588289,0.00003408313],"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":[0.000001774377,0.000008197768,0.0002888973,0.0002250591,8.096424e-7,3.507131e-8,0.0001555419,0.012846,0.7718982,0.001072488,8.163375e-7,0.2135022],"study_design_scores_gemma":[0.0001917806,0.00004064224,0.009649278,0.0002379542,0.00001053459,0.00002307497,0.0002817594,0.04386579,0.9432753,0.0003556706,0.001867761,0.0002004733],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9592835,0.00401652,0.03582318,0.0001575228,0.000109939,0.0001479537,6.787951e-7,0.0002072612,0.0002533832],"genre_scores_gemma":[0.9976345,0.0002584775,0.002000789,0.000003758078,0.00006881518,0.00001613906,0.00000429387,0.000008132535,0.000005087527],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2133017,"threshold_uncertainty_score":0.3424155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003755105063697716,"score_gpt":0.230013710458895,"score_spread":0.2262586053951973,"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."}}