{"id":"W2946142791","doi":"10.5740/jaoacint.18-0318","title":"DNA Quality and Quantity Analysis of <i>Camellia sinensis</i> Through Processing from Fresh Leaves to a Green Tea Extract","year":2019,"lang":"en","type":"article","venue":"Journal of AOAC International","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Camellia sinensis; genomic DNA; DNA; Biology; Green tea; Polymerase chain reaction; Food science; Botany; Gene; Genetics","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":[0.0002316421,0.00008974207,0.0002372697,0.00009542095,0.00002286243,0.00001853847,0.0002209732,0.00009637767,0.00005614944],"category_scores_gemma":[0.00005917695,0.00007712411,0.000162026,0.0001277629,0.0000479337,0.00001175913,0.00007980895,0.00009015739,0.000001501261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001526807,"about_ca_system_score_gemma":0.00004264298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001958019,"about_ca_topic_score_gemma":0.00008582388,"domain_scores_codex":[0.9991133,0.00004069273,0.0004118868,0.0001799053,0.0001748832,0.00007937157],"domain_scores_gemma":[0.9990412,0.00002034766,0.0004161927,0.0001625739,0.0003162901,0.00004340453],"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":[0.0001077157,0.0000830338,0.08227848,0.000006158019,0.0005817555,0.000001225342,0.00005696339,0.00006398101,0.9143761,0.0004794274,0.0004488262,0.001516288],"study_design_scores_gemma":[0.00059196,0.0003550826,0.3729641,0.00005667151,0.0003752556,0.00002269552,0.0001485025,0.0003472407,0.5960701,0.001038206,0.02778046,0.0002497266],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9694971,0.0003001004,0.02881104,0.0008054318,0.00005827159,0.00007049372,0.0001007881,0.000002897896,0.000353829],"genre_scores_gemma":[0.9864676,0.0001097716,0.01261964,0.0005340899,0.0001132675,0.000002095342,0.00006638554,0.000006752069,0.00008036989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.318306,"threshold_uncertainty_score":0.314503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0195237073706422,"score_gpt":0.3421025781091684,"score_spread":0.3225788707385263,"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."}}