{"id":"W3120529550","doi":"10.1007/s10658-020-02189-1","title":"Impact of DNA extraction efficiency on the sensitivity of PCR-based plant disease diagnosis and pathogen quantification","year":2021,"lang":"en","type":"article","venue":"European Journal of Plant Pathology","topic":"Plant Disease Resistance and Genetics","field":"Agricultural and Biological Sciences","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture Food and Rural Development; Alberta Ministry of Agriculture and Forestry","funders":"","keywords":"Biology; Pathogen; DNA extraction; DNA; Polymerase chain reaction; Microbiology; Plant disease; Botrytis; Botrytis cinerea; Botany; Biotechnology; Genetics; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01147856,0.001520494,0.001486266,0.001129724,0.0005092089,0.002024054,0.0009576214,0.001746112,0.002472977],"category_scores_gemma":[0.02211972,0.001657735,0.0007255186,0.0009647985,0.00117125,0.001453811,0.001063482,0.001572996,0.002037806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005321255,"about_ca_system_score_gemma":0.0006314471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007818908,"about_ca_topic_score_gemma":0.001657688,"domain_scores_codex":[0.9813297,0.007277983,0.001701642,0.004694218,0.004200713,0.0007956274],"domain_scores_gemma":[0.9692833,0.02457484,0.001098324,0.001933535,0.002865119,0.0002449784],"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":[0.0005796471,0.0001079631,0.002363499,0.0002716178,0.00006302543,0.00003512614,0.0001269669,0.0006263371,0.9833349,0.0001666515,0.0001180123,0.01220627],"study_design_scores_gemma":[0.00001662385,0.0004231716,0.003991374,0.00004314861,0.000134545,0.0001495185,0.00003534523,0.005744806,0.9870771,0.0001884947,0.002164257,0.000031552],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6998806,0.01771813,0.2706564,0.001294688,0.000854546,0.0008414134,0.001721276,0.001791903,0.005241068],"genre_scores_gemma":[0.7704307,0.004850759,0.2144418,0.0009269869,0.0001702854,0.0006074064,0.002622656,0.0006481693,0.005301362],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01147856,"threshold_uncertainty_score":0.06070513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03557390226922423,"score_gpt":0.2437394014689816,"score_spread":0.2081654991997574,"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."}}