{"id":"W2019686544","doi":"10.1111/j.1745-4530.2006.00092.x","title":"ENZYMATIC HYDROLYSIS PRETREATMENT TO SOLVENT EXTRACTION OF SOYBROKENS FOR ENHANCED OIL AVAILABILITY AND EXTRACTABILITY","year":2006,"lang":"en","type":"article","venue":"Journal of Food Process Engineering","topic":"Proteins in Food Systems","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Hydrolysis; Chemistry; Enzymatic hydrolysis; Chromatography; Extraction (chemistry); Solvent; Moisture; Water content; 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":[0.0002881734,0.0006913182,0.0007655282,0.0003122194,0.0001809139,0.0002769909,0.0001738378,0.0002524663,0.001126942],"category_scores_gemma":[0.0004176505,0.000256026,0.0005193913,0.0004390721,0.0002266041,0.0002441874,0.000145167,0.0004987441,0.0004120496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001803618,"about_ca_system_score_gemma":0.0003369806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001339898,"about_ca_topic_score_gemma":0.00300936,"domain_scores_codex":[0.9997577,0.00004654592,0.00002536181,0.00004073762,0.00007967099,0.00004997298],"domain_scores_gemma":[0.999755,0.0000851982,0.00005284903,0.00001591845,0.00006488427,0.00002623295],"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":[0.00003635797,0.000006254271,0.00004043373,0.00002029223,0.000002500605,0.00001083227,0.000003382941,0.00002336846,0.9995066,0.000003453666,0.000004214428,0.0003423816],"study_design_scores_gemma":[0.000002400184,0.00008606286,0.001567969,0.00000286079,0.000008387123,0.00003423906,0.00001106022,0.0001666526,0.9977911,0.000004865356,0.0003214317,0.000002880979],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9794624,0.001769004,0.01729215,0.00007610257,0.00002895754,0.0000783483,0.0004024446,0.00008892974,0.0008016992],"genre_scores_gemma":[0.9787349,0.00114457,0.0169977,0.00005957622,0.00001139694,0.00006710022,0.001110829,0.00006084106,0.001813158],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001339898,"threshold_uncertainty_score":0.003769994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01226665582796629,"score_gpt":0.2303428425929216,"score_spread":0.2180761867649553,"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."}}