{"id":"W2775076633","doi":"10.1094/pdis-08-17-1222-re","title":"Development and Application of a Multiplex qPCR Method for the Simultaneous Detection and Quantification of <i>Pratylenchus alleni</i> and <i>P. penetrans</i> in Quebec, Canada","year":2017,"lang":"en","type":"article","venue":"Plant Disease","topic":"Nematode management and characterization studies","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cégep Saint-Jean-sur-Richelieu; Grain Research Centre; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada; Ministère de l'Agriculture, des Pêcheries et de l'Alimentation","keywords":"Biology; Pratylenchus penetrans; Larva; Nematode; Multiplex polymerase chain reaction; Population density; Veterinary medicine; Agronomy; Population; Zoology; Ecology; Polymerase chain reaction; Genetics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009683051,0.00005306689,0.00008367073,0.000005397767,0.0001895527,0.00002497316,0.00005416568,0.0000127615,7.062295e-7],"category_scores_gemma":[0.00004348721,0.00002247405,0.00000750022,0.00002147509,0.00003438394,0.00004392544,0.00002542776,0.000013772,2.239281e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004904852,"about_ca_system_score_gemma":0.000008232378,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08898877,"about_ca_topic_score_gemma":0.8570464,"domain_scores_codex":[0.9996164,0.00001353338,0.0001281865,0.0001211792,0.0000659595,0.00005472249],"domain_scores_gemma":[0.9995351,0.0002509326,0.0001214248,0.0000387313,0.00002601216,0.00002774386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004856429,0.00007374841,0.0361736,0.0003240545,0.00004269521,0.000001881397,0.0005732041,0.00004665289,0.4000607,0.0003119979,0.00003915334,0.5618666],"study_design_scores_gemma":[0.0002716032,0.00001247595,0.9640754,0.00002345419,0.00003606415,4.122876e-7,0.0007029506,0.01680315,0.007986262,0.00003472866,0.009957818,0.00009568977],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969119,0.0003303825,0.001468694,0.0007610752,0.00001517751,0.0003924126,0.000109968,0.000003625493,0.000006734885],"genre_scores_gemma":[0.9994916,0.0002234945,0.0001328538,0.0000278896,0.000008484581,0.00005374318,0.00003604362,4.200465e-7,0.00002551279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9279018,"threshold_uncertainty_score":0.9170777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0189452143430977,"score_gpt":0.2309129572875797,"score_spread":0.211967742944482,"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."}}