{"id":"W2171924090","doi":"10.1093/ps/82.4.648","title":"Investigating the possibility of monitoring lectin levels in commercial soybean meals intended for poultry feeding using steam-heated soybean meal as a model","year":2003,"lang":"en","type":"article","venue":"Poultry Science","topic":"Animal Nutrition and Physiology","field":"Agricultural and Biological Sciences","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Chemistry; Soybean meal; Lectin; Food science; Denaturation (fissile materials); Meal; Raw material; Biochemistry; Nuclear chemistry; 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":[0.0002134286,0.000268935,0.0002123951,0.00009766361,0.00007997681,0.0002197075,0.0001562449,0.0002797166,0.0003837861],"category_scores_gemma":[0.0002848849,0.0001042958,0.0001738587,0.0001097647,0.0001932331,0.0001978717,0.00009575042,0.000298351,0.0001377927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000244719,"about_ca_system_score_gemma":0.0001174788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006618548,"about_ca_topic_score_gemma":0.001499518,"domain_scores_codex":[0.9999377,0.00001369634,0.000004174042,0.00001873734,0.00001611327,0.000009590463],"domain_scores_gemma":[0.9998252,0.00004366208,0.00006736928,0.000009561086,0.00003217292,0.00002209863],"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":[0.0001449283,0.00001935722,0.002121674,0.00003330334,0.000005710449,0.00001434929,0.00001017928,0.00005144818,0.9967844,0.000006691189,0.000005359357,0.0008025064],"study_design_scores_gemma":[0.000009504652,0.001783941,0.07022015,0.000009434159,0.00004619204,0.0001980395,0.00008414045,0.002243252,0.9247634,0.00003848126,0.0005942836,0.000009114195],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965079,0.0004573957,0.002781293,0.00001861394,0.000005989073,0.00001272657,0.00006472463,0.00001606916,0.0001353276],"genre_scores_gemma":[0.9896756,0.0004239665,0.00906722,0.00005540088,0.000005253878,0.00002154863,0.0002487275,0.00001105497,0.0004911983],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006618548,"threshold_uncertainty_score":0.001775563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1550877548493899,"score_gpt":0.3427156956727705,"score_spread":0.1876279408233806,"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."}}