{"id":"W4210644796","doi":"10.3390/biology11020201","title":"Increasing the Efficiency of Canola and Soybean GMO Detection and Quantification Using Multiplex Droplet Digital PCR","year":2022,"lang":"en","type":"article","venue":"Biology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Digital polymerase chain reaction; Canola; Biology; Multiplex; Real-time polymerase chain reaction; Genetically modified organism; Duplex (building); Multiplex polymerase chain reaction; Computational biology; Molecular biology; Gene; Biotechnology; Genetics; Polymerase chain reaction; Food science; DNA","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":[0.0001427978,0.00005593426,0.00006027869,0.00002612846,0.0001271264,0.000008746957,0.00005028358,0.00003669053,0.000001938717],"category_scores_gemma":[0.00006138092,0.00004698336,0.00001619396,0.00004758869,0.00007954388,0.000001479939,0.0001084879,0.00004336847,7.58197e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006049443,"about_ca_system_score_gemma":0.00001313012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001400009,"about_ca_topic_score_gemma":0.00002571122,"domain_scores_codex":[0.9995888,0.00004707631,0.00009798613,0.0001503934,0.00002730733,0.00008842019],"domain_scores_gemma":[0.9997982,0.00002077685,0.00004203081,0.0001066405,0.00001551862,0.00001682626],"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":[0.00002332291,0.000008870946,0.009306086,0.000005129782,0.000007868309,1.198441e-7,0.00006032874,0.0001913243,0.986064,0.00001899314,0.000001700772,0.004312319],"study_design_scores_gemma":[0.0007262903,0.0006360662,0.0423785,0.000006179107,0.00003605061,0.0003472213,0.001048445,0.02177844,0.9234225,0.00007828859,0.009244813,0.0002972402],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9855539,0.0009844889,0.01322886,0.00002079804,0.00008020706,0.00008255791,0.0000209446,0.000004425609,0.00002385414],"genre_scores_gemma":[0.9997457,0.00002957399,0.0001308006,0.00001313827,0.00003659003,0.000005384211,0.00002534324,0.000006053301,0.000007443044],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06264147,"threshold_uncertainty_score":0.1915926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01267930925435478,"score_gpt":0.288831256739953,"score_spread":0.2761519474855982,"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."}}