{"id":"W4308306241","doi":"10.1016/j.tifs.2022.10.016","title":"Novel Extraction technologies for developing plant protein ingredients with improved functionality","year":2022,"lang":"en","type":"article","venue":"Trends in Food Science & Technology","topic":"Proteins in Food Systems","field":"Agricultural and Biological Sciences","cited_by":154,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Extraction (chemistry); Protein purification; Biochemical engineering; Process engineering; Computer science; Biotechnology; Chromatography; Engineering; Chemistry; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001020323,0.0001971796,0.0002376958,0.0006132709,0.001024061,0.00005116441,0.001179409,0.0001539043,0.0000231375],"category_scores_gemma":[0.0001695573,0.00009371105,0.00004209804,0.005613589,0.0006427787,0.0002669794,0.0005663159,0.0004136388,0.000001430084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005121017,"about_ca_system_score_gemma":0.00007740455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007905086,"about_ca_topic_score_gemma":0.0009727922,"domain_scores_codex":[0.9977172,0.00002581287,0.0003468379,0.0007912094,0.000470536,0.0006483881],"domain_scores_gemma":[0.9993719,0.00004859039,0.0002521155,0.0001898342,0.0001085618,0.00002901208],"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":[0.0001087961,0.0001471049,0.001473056,0.000005999211,0.000008926326,0.000002068929,0.00003603423,0.00002811613,0.8421457,0.0100694,0.0000178634,0.1459569],"study_design_scores_gemma":[0.002592851,0.01556223,0.02734063,0.0001421297,0.00001911367,0.0006708859,0.01285538,0.002285717,0.8511952,0.0218443,0.06373076,0.001760846],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928022,0.00008663664,0.0006062792,0.004306165,0.0002786556,0.0008186324,0.0001431483,0.0007464343,0.0002118494],"genre_scores_gemma":[0.9946701,8.946629e-7,0.003060107,0.00002826623,0.0000252186,0.00208786,0.0000309979,0.000002202884,0.00009436993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1441961,"threshold_uncertainty_score":0.7876351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05500441054792181,"score_gpt":0.2723147740759251,"score_spread":0.2173103635280033,"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."}}