{"id":"W2073547683","doi":"10.1007/s11746-011-1849-1","title":"Single Soybean Seed NMR Calibration for Oil Measurement Using Commercial Cooking Oils","year":2011,"lang":"en","type":"article","venue":"Journal of the American Oil Chemists Society","topic":"Soybean genetics and cultivation","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Ontario Ministry of Agriculture, Food and Rural Affairs","keywords":"Soybean oil; Biodiesel; Cooking oil; Cultivar; Calibration; Calibration curve; Chemistry; Vegetable oil; Environmental science; Pulp and paper industry; Agronomy; Food science; Mathematics; Chromatography; Biology; Organic chemistry; Engineering; Detection limit","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002158736,0.0006810215,0.0004463039,0.0008323919,0.0004057002,0.0003655231,0.000666973,0.0005468503,0.001111506],"category_scores_gemma":[0.002659825,0.0003636558,0.0003333719,0.0005733502,0.0003688729,0.0003586127,0.0004736999,0.0004976591,0.0005895285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006249761,"about_ca_system_score_gemma":0.0005179032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0018497,"about_ca_topic_score_gemma":0.006142346,"domain_scores_codex":[0.9984982,0.0003337147,0.00007749547,0.0003837975,0.0006431942,0.00006356131],"domain_scores_gemma":[0.9982168,0.0005317933,0.0003188893,0.0002266117,0.0006180314,0.00008779357],"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":[0.00006135414,0.00002531662,0.001174176,0.00003519853,0.00001074271,0.0000102382,0.00002007404,0.000191606,0.9939899,0.00003638061,0.00002845434,0.004416453],"study_design_scores_gemma":[0.00001274395,0.0003993762,0.005713179,0.00001081702,0.00004028868,0.000150263,0.00002816635,0.005726344,0.986922,0.00004585811,0.0009355504,0.00001548286],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6880739,0.0008947371,0.3073501,0.0001044182,0.00008986113,0.000227669,0.0004377231,0.001208608,0.001612958],"genre_scores_gemma":[0.7253473,0.0005768081,0.2711752,0.00008670612,0.00001660243,0.0002337821,0.0005967855,0.0001897473,0.001777039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002158736,"threshold_uncertainty_score":0.01141661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08533832871838617,"score_gpt":0.2422320531993768,"score_spread":0.1568937244809906,"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."}}