{"id":"W2285911513","doi":"10.1038/srep22181","title":"Dedicated Industrial Oilseed Crops as Metabolic Engineering Platforms for Sustainable Industrial Feedstock Production","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Lipid metabolism and biosynthesis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Saskatchewan Research Council (Canada)","funders":"National Institute of Food and Agriculture; FP7 Food, Agriculture and Fisheries, Biotechnology; National Research Council Canada; Sveriges Lantbruksuniversitet; Svenska Forskningsrådet Formas; VINNOVA; Stiftelsen för Strategisk Forskning; U.S. Department of Agriculture; Ministry of Agriculture - Saskatchewan; Vetenskapsrådet; National Science Foundation","keywords":"Raw material; Sustainable production; Production (economics); Industrial production; Biotechnology; Metabolic engineering; Agricultural engineering; Environmental science; Engineering; Biology; Economics","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":[0.001648032,0.0002204489,0.0002451877,0.0001887609,0.0003207763,0.0001562176,0.000190707,0.0002432124,0.00003679575],"category_scores_gemma":[0.003338813,0.000147112,0.0001435797,0.0003643801,0.000145134,0.00004140599,0.0001271339,0.00008691088,0.00001199424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002884916,"about_ca_system_score_gemma":0.0005386604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002694996,"about_ca_topic_score_gemma":0.000005758448,"domain_scores_codex":[0.9976596,0.00001820956,0.0005037104,0.000896042,0.0003363892,0.0005860786],"domain_scores_gemma":[0.9984335,0.00001638921,0.0002797996,0.0007431575,0.0003404245,0.0001867268],"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":[0.0001476556,0.00006819842,0.001049324,0.00001513901,0.00007242283,0.00001910209,0.00002657349,0.00001014387,0.9626253,0.0001198765,0.02444605,0.01140017],"study_design_scores_gemma":[0.000379618,0.00003087237,0.00009799735,0.00001370073,0.00003287944,0.00005193008,0.00003195263,0.000001628534,0.5667411,0.0001375926,0.4323315,0.0001492135],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903113,0.0002092868,0.0003274834,0.0001735471,0.007997856,0.0007892219,0.00000521065,0.00005669649,0.0001294309],"genre_scores_gemma":[0.9727301,0.00001007074,0.0002336999,0.00001484892,0.002967668,0.0001334087,0.0001182843,0.00003466395,0.02375725],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4078855,"threshold_uncertainty_score":0.5999052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01732438430163489,"score_gpt":0.2259159487027545,"score_spread":0.2085915644011196,"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."}}