{"id":"W3014624313","doi":"10.1038/s41438-020-0261-0","title":"Coriander Genomics Database: a genomic, transcriptomic, and metabolic database for coriander","year":2020,"lang":"en","type":"article","venue":"Horticulture Research","topic":"Plant Gene Expression Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Fredericton; Agriculture and Agri-Food Canada","funders":"National Natural Science Foundation of China","keywords":"Biology; Coriandrum; Apiaceae; Genome; Genomics; Proteogenomics; Gene; Functional genomics; Database; Comparative genomics; Sativum; Transcriptome; Genetics; Computational biology; Botany; Gene expression","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":[0.0005882562,0.0002164398,0.0002982574,0.00006895197,0.0002491357,0.0001067878,0.000364123,0.0001805593,0.00007169604],"category_scores_gemma":[0.0003357298,0.0001754717,0.000120514,0.0002133903,0.0001422155,0.0000134461,0.0002842866,0.0002880731,0.00002452029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001618946,"about_ca_system_score_gemma":0.0001612171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001836458,"about_ca_topic_score_gemma":0.00008978891,"domain_scores_codex":[0.9979038,0.000182102,0.0002796066,0.0007681571,0.0003326453,0.0005336979],"domain_scores_gemma":[0.9987415,0.00004874539,0.0000547683,0.0004516853,0.0002502168,0.0004530676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003841068,0.00003662666,0.0001796681,0.00004851686,0.0001721624,0.000007231515,0.0001955544,0.00001132163,0.8523528,0.0001566403,0.1460973,0.0003580891],"study_design_scores_gemma":[0.001138906,0.0001134714,0.0002323136,0.000008519123,0.00009132623,0.00001693967,0.0003736723,0.0008821739,0.3508907,0.00001582626,0.6460043,0.0002319098],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.950285,0.01465829,0.02325531,0.005591741,0.0002379478,0.001933427,0.003184382,0.00005417825,0.0007997714],"genre_scores_gemma":[0.9756082,0.00806031,0.006198398,0.001628674,0.001693018,0.0002220965,0.004593646,0.00008245093,0.001913243],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5014622,"threshold_uncertainty_score":0.7155529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07519983342525158,"score_gpt":0.3472170513727788,"score_spread":0.2720172179475272,"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."}}