{"id":"W2106535627","doi":"10.1128/jcm.02484-09","title":"Rapid Identification and Differentiation of <i>Mycobacterium avium</i> Subspecies <i>paratuberculosis</i> Types by Use of Real-Time PCR and High-Resolution Melt Analysis of the MAP1506 Locus","year":2010,"lang":"en","type":"article","venue":"Journal of Clinical Microbiology","topic":"Mycobacterium research and diagnosis","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Universidad Complutense de Madrid; Natural Sciences and Engineering Research Council of Canada; College of Veterinary Medicine, University of Minnesota; University of Minnesota; McGill University; AgResearch","keywords":"High Resolution Melt; Amplicon; Mycobacterium avium subspecies paratuberculosis; Paratuberculosis; Biology; Subspecies; Polymerase chain reaction; Mycobacterium; Locus (genetics); Genetics; Gene; Virology; Microbiology; Bacteria","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":[0.0004788629,0.0004423344,0.0002648434,0.0008519162,0.0001860914,0.0005005059,0.000377017,0.0006858302,0.001024462],"category_scores_gemma":[0.00129084,0.0002611465,0.0003011485,0.0002948565,0.0003430584,0.0004995377,0.0003753371,0.0008192698,0.0008835955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001393492,"about_ca_system_score_gemma":0.0001183509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003853543,"about_ca_topic_score_gemma":0.0005075146,"domain_scores_codex":[0.9995011,0.00009272815,0.00005040936,0.0001345224,0.000152032,0.00006922436],"domain_scores_gemma":[0.9993989,0.0001837808,0.0001691915,0.00006207551,0.0001267969,0.00005925512],"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":[0.0001199283,0.00004867625,0.008441254,0.00006694435,0.000005167928,0.0001311614,0.0001053474,0.00006043155,0.9749324,0.0001271391,0.0001276937,0.01583395],"study_design_scores_gemma":[0.00002942699,0.0006559977,0.05671742,0.00004383604,0.00004313939,0.004788763,0.0002744206,0.003067333,0.9289762,0.000490818,0.004878796,0.00003366554],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.88411,0.002722405,0.1077629,0.0004749506,0.00009255773,0.0002623714,0.0009395619,0.0006552579,0.002980049],"genre_scores_gemma":[0.8721381,0.001223732,0.1236967,0.0001346832,0.00004315749,0.0001325256,0.001163011,0.0000750917,0.001392939],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001024462,"threshold_uncertainty_score":0.003427148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02524956025504531,"score_gpt":0.3070883674177169,"score_spread":0.2818388071626716,"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."}}