{"id":"W2329888261","doi":"10.1021/jf500610w","title":"Influence of Amount of Starting Material for DNA Extraction on Detection of Low-Level Presence of Genetically Engineered Traits","year":2014,"lang":"en","type":"article","venue":"Journal of Agricultural and Food Chemistry","topic":"Genetically Modified Organisms Research","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"DNA extraction; Canola; Extraction (chemistry); DNA; Replicate; Genetically modified organism; Biology; Chromatography; Biotechnology; Polymerase chain reaction; Chemistry; Agronomy; Genetics; Mathematics; Gene; Statistics","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":[0.0002210771,0.0001000727,0.0002665833,0.00001024011,0.00002813866,0.000009333527,0.0001623938,0.0001103233,0.0000145302],"category_scores_gemma":[0.0002762957,0.00003906268,0.00009553649,0.0001125792,0.00008394159,0.00006538663,0.00002991338,0.0001021974,6.383951e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000011193,"about_ca_system_score_gemma":0.00001031152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008282006,"about_ca_topic_score_gemma":0.00000488655,"domain_scores_codex":[0.9988385,0.00002655496,0.0005636084,0.000110372,0.0003241097,0.0001368592],"domain_scores_gemma":[0.9986205,0.0002034869,0.0005109883,0.00003082609,0.0005564594,0.00007776095],"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":[0.0001703136,0.00009353682,0.00007682279,0.000231096,0.00002398663,7.433686e-8,0.00004418819,0.000634976,0.9926813,0.000008590897,0.000003745854,0.0060314],"study_design_scores_gemma":[0.0001812749,0.00116576,0.294486,0.00008846421,0.00001439677,0.000009178473,0.0001066393,0.0000235682,0.7037996,0.0000717321,0.000004212968,0.00004919722],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996529,0.00003035327,0.00004217853,0.00007178713,0.0000232694,0.00009757392,0.0000619224,0.000002395945,0.00001764338],"genre_scores_gemma":[0.9994578,0.00002193827,0.0003761881,0.000002229179,0.0001270314,0.000001897626,0.00000360335,9.170034e-7,0.000008420152],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2944091,"threshold_uncertainty_score":0.159293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01546568897439455,"score_gpt":0.2149655645474818,"score_spread":0.1994998755730872,"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."}}