{"id":"W2384795605","doi":"","title":"Optimization of extracting condition for rice bran protein with protamex","year":2008,"lang":"en","type":"article","venue":"Food Science and Technology International","topic":"Enzyme Production and Characterization","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Bran; Chemistry; Food science; Moisture; Hydrolysis; Cellulose; Chromatography; Enzyme; Composition (language); Enzymatic hydrolysis; Biochemistry; Raw material; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001049249,0.00004503946,0.00004134553,0.0001390667,0.0001215247,0.000008091495,0.0001068096,0.00005413365,0.000004347585],"category_scores_gemma":[0.0001779742,0.00004048648,0.000007310532,0.0002048715,0.0003587662,0.00002248754,0.00002691786,0.00003297297,2.19086e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009135432,"about_ca_system_score_gemma":0.00008835837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.456022e-7,"about_ca_topic_score_gemma":7.245406e-7,"domain_scores_codex":[0.9995276,0.000003430133,0.00008947234,0.0001897083,0.0001183016,0.0000715309],"domain_scores_gemma":[0.9993179,0.000001924474,0.00009701187,0.00007658941,0.0004926968,0.00001386792],"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":[0.00003489954,0.00003122232,0.001954377,0.000006957797,0.00001105936,1.765208e-7,0.00002681293,0.0001206799,0.9957946,0.001367242,0.00002010063,0.0006318981],"study_design_scores_gemma":[0.0003777369,0.0005320673,0.001119797,0.00001141042,0.00000286723,0.00006932578,0.00008001235,0.001058365,0.9954305,0.00009325476,0.001159879,0.00006474335],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9651813,0.0000181788,0.03333342,0.0009115842,0.00005968809,0.0002633513,0.00001033229,0.00001619362,0.0002059725],"genre_scores_gemma":[0.9919838,0.00001020629,0.007716162,0.00002549784,0.00003907985,0.00007485676,0.00004174305,0.000004004182,0.0001046897],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02680248,"threshold_uncertainty_score":0.1650991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009819976240079681,"score_gpt":0.2427358623187842,"score_spread":0.2329158860787045,"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."}}