{"id":"W2127102113","doi":"10.2807/1560-7917.es2013.18.35.20566","title":"Proof-of-concept study for successful inter-laboratory comparison of MLVA results","year":2013,"lang":"en","type":"article","venue":"Eurosurveillance","topic":"Salmonella and Campylobacter epidemiology","field":"Agricultural and Biological Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centers for Disease Control and Prevention; Public Health England; Danmarks Tekniske Universitet; Public Health Agency; Public Health Agency of Canada; Bundesinstitut für Risikobewertung; Robert Koch Institut; Akershus Universitetssykehus; Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology; Queensland Health; National Health Laboratory Service; Statens veterinärmedicinska anstalt; Johns Hopkins University","keywords":"Multiple Loci VNTR Analysis; Typing; Computational biology; Variable number tandem repeat; Computer science; Genetics; Biology; Allele","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02262002,0.002594219,0.001458807,0.0010081,0.0007195056,0.001580274,0.002238867,0.002998959,0.004734283],"category_scores_gemma":[0.01376967,0.0008975732,0.001184085,0.0005360536,0.001283454,0.001279362,0.001817438,0.002309463,0.002716394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008849276,"about_ca_system_score_gemma":0.001840259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003768999,"about_ca_topic_score_gemma":0.0002729079,"domain_scores_codex":[0.9853892,0.004997978,0.0007921411,0.002184831,0.005756741,0.0008792662],"domain_scores_gemma":[0.9854516,0.003859613,0.002767007,0.001758074,0.005170273,0.0009933116],"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":[0.001402051,0.00203748,0.001182164,0.001070947,0.0001882126,0.0003868694,0.0002450009,0.001634875,0.9612171,0.001360467,0.001943547,0.02733127],"study_design_scores_gemma":[0.0008522729,0.01298153,0.002829054,0.0001243315,0.0001826682,0.001138143,0.0001557441,0.00957342,0.9508206,0.0004827007,0.02073879,0.000120749],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2876183,0.002135772,0.6855365,0.001336226,0.00133586,0.01465757,0.001984749,0.002205917,0.003189217],"genre_scores_gemma":[0.449185,0.001208813,0.5270013,0.0009530141,0.0002413999,0.01410715,0.002684568,0.0003455695,0.004273152],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02262002,"threshold_uncertainty_score":0.1196275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04021626771522425,"score_gpt":0.292387891573671,"score_spread":0.2521716238584468,"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."}}