{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001337063,0.001016295,0.0009968826,0.001167928,0.0002291682,0.0008394027,0.0008132503,0.0008684604,0.001526976],"category_scores_gemma":[0.001880902,0.0006463896,0.00121668,0.0006326386,0.000485822,0.0006051787,0.001320477,0.00164534,0.001192402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005276127,"about_ca_system_score_gemma":0.0004268464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005104613,"about_ca_topic_score_gemma":0.001235955,"domain_scores_codex":[0.9984566,0.0002603394,0.00007542856,0.0006753134,0.0003472332,0.0001850383],"domain_scores_gemma":[0.9990989,0.0003999407,0.0001853353,0.000123813,0.0001325814,0.00005948779],"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":[0.0001061916,0.0000723562,0.002825385,0.0001946185,0.00002797263,0.00004562873,0.00003766111,0.0008256791,0.9778728,0.0003308479,0.0002926142,0.01736813],"study_design_scores_gemma":[0.00003352291,0.0004450491,0.01998161,0.00002796676,0.00009874199,0.0005181131,0.00004415792,0.01426735,0.9571126,0.0005369807,0.006885212,0.00004883787],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4092028,0.003290053,0.5632358,0.0006652548,0.0001747668,0.0007763677,0.01175091,0.006363729,0.004540331],"genre_scores_gemma":[0.3620715,0.001139022,0.6192132,0.0008509663,0.00003280985,0.0004342261,0.01178554,0.0002737468,0.004198896],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001526976,"threshold_uncertainty_score":0.007071137,"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."}}