{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006506646,0.001041791,0.000896653,0.0003652312,0.0003013981,0.0005279054,0.0003943812,0.0004222399,0.001159884],"category_scores_gemma":[0.0008177882,0.0003377849,0.0004109439,0.0005763933,0.0002358057,0.0004641022,0.0003240207,0.000520752,0.0008735005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002339189,"about_ca_system_score_gemma":0.0003259668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006435813,"about_ca_topic_score_gemma":0.001377955,"domain_scores_codex":[0.9994987,0.000121709,0.00006977411,0.0001389302,0.0001053792,0.00006547974],"domain_scores_gemma":[0.9997105,0.0000924976,0.00006121874,0.00001964784,0.00008056773,0.00003555037],"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":[0.0001443377,0.0000397583,0.0002414018,0.00008430635,0.000007823188,0.00005549172,0.00003148358,0.00005616999,0.9979827,0.00001737578,0.00006354068,0.001275544],"study_design_scores_gemma":[0.00002203667,0.0002175014,0.00414217,0.00001249362,0.00004825648,0.0002639348,0.00003978057,0.0005561822,0.9919518,0.00001791856,0.002710957,0.000017071],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9585092,0.002542908,0.03459532,0.0003235767,0.0001212272,0.0005441968,0.0009673501,0.0004072286,0.001989004],"genre_scores_gemma":[0.8521683,0.003581562,0.1288982,0.0003239323,0.00008832839,0.001007393,0.006629411,0.0004794938,0.006823456],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001159884,"threshold_uncertainty_score":0.003880203,"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."}}