{"id":"W4398238526","doi":"10.1021/acs.jafc.4c00380","title":"Decoding the Duality of Antinutrients: Assessing the Impact of Protein Extraction Methods on Plant-Based Protein Sources","year":2024,"lang":"en","type":"article","venue":"Journal of Agricultural and Food Chemistry","topic":"Phytase and its Applications","field":"Agricultural and Biological Sciences","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Agriculture and Agri-Food Canada","funders":"Consejo Nacional de Ciencia y Tecnología; University of Leeds","keywords":"Phytic acid; Protein purification; Extraction (chemistry); Antinutrient; Plant protein; Trypsin; Rice protein; Biology; Biochemistry; Food science; Chemistry; Biotechnology; Chromatography; Enzyme","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":[0.0004604076,0.0001020107,0.0001598595,0.000005507656,0.0001443479,0.00008894561,0.0001597065,0.00005797304,0.000021991],"category_scores_gemma":[0.00005283467,0.00002181133,0.0001886412,0.0002354868,0.00006794326,0.0001374625,0.00002008096,0.0002286606,1.682145e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001872143,"about_ca_system_score_gemma":0.0000180043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002425046,"about_ca_topic_score_gemma":0.000001578455,"domain_scores_codex":[0.9992287,0.00007503299,0.0003218008,0.00009746285,0.0001758156,0.0001011572],"domain_scores_gemma":[0.9991748,0.0002598818,0.0003804236,0.00003811092,0.000105135,0.00004166619],"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":[0.00001534272,0.00007570573,0.000186628,0.00004292261,0.00005119025,3.305369e-7,0.00005534353,0.00001562715,0.9903522,0.00002238919,0.0001102294,0.009072166],"study_design_scores_gemma":[0.00007111304,0.0002622379,0.08159102,0.0003172149,0.00003111189,0.00004050257,0.0008126826,0.00003819841,0.9162279,0.000231263,0.0003128816,0.00006387624],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977241,0.0009061286,0.00001688186,0.0009973177,0.00001656853,0.0001381003,0.00004972212,0.000006951057,0.0001442046],"genre_scores_gemma":[0.999578,0.00002048916,0.0001416869,0.000006675996,0.0002100967,0.000006362537,0.00000994853,5.733687e-7,0.00002618863],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08140439,"threshold_uncertainty_score":0.1110222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03238414514377576,"score_gpt":0.3299658527194219,"score_spread":0.2975817075756461,"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."}}