{"id":"W2788216798","doi":"10.7717/peerj.4392","title":"Genome-Enhanced Detection and Identification (GEDI) of plant pathogens","year":2018,"lang":"en","type":"article","venue":"PeerJ","topic":"Plant Pathogens and Resistance","field":"Agricultural and Biological Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"FPInnovations; Simon Fraser University; BC Cancer Agency; Université Laval; Natural Resources Canada; Canadian Food Inspection Agency; Canadian Forest Service; Biopterre; University of British Columbia","funders":"Genome British Columbia; Canadian Forest Service; Canadian Food Inspection Agency; Genome Canada","keywords":"Genome; Biology; Oomycete; Computational biology; Identification (biology); Genomics; DNA sequencing; Genetics; Evolutionary biology; Gene; Ecology","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":[0.0001191818,0.00004643858,0.00007168272,0.000006480651,0.0001009948,0.00001341553,0.00005536512,0.00003823718,0.00004215917],"category_scores_gemma":[0.00001992456,0.00001768918,0.0000211709,0.00009722106,0.00005168051,0.0000349987,0.00001506204,0.00002431909,0.00001268419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004969866,"about_ca_system_score_gemma":0.000001438059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001609529,"about_ca_topic_score_gemma":0.0004311094,"domain_scores_codex":[0.9995627,0.00001734489,0.0001105317,0.0001340046,0.00008700533,0.00008839315],"domain_scores_gemma":[0.9997917,0.00002658939,0.0000669919,0.0000285862,0.00005576169,0.00003031524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00001541,0.00001005515,0.0002792911,0.000003810833,0.000002409273,4.932623e-7,0.00005013338,1.130221e-7,0.9838827,0.00001444841,0.00001007583,0.01573104],"study_design_scores_gemma":[0.00003576364,0.00007972393,0.6953702,0.000005629262,0.000005581596,0.000005512397,0.00009238835,0.00004302465,0.2999745,0.00009023092,0.004241876,0.00005558291],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989012,0.0001194512,0.0001140673,0.00005467148,0.00009085325,0.00006560782,0.0002205391,0.00001883921,0.0004147304],"genre_scores_gemma":[0.9994501,0.00007601664,0.00003363659,0.00001383805,0.0001641478,0.00000367082,0.00003677399,3.017008e-7,0.0002215346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6950909,"threshold_uncertainty_score":0.07767808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0125245643022304,"score_gpt":0.1953549477955469,"score_spread":0.1828303834933165,"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."}}