{"id":"W2120967220","doi":"10.2807/1560-7917.es2013.18.35.20565","title":"Development and application of MLVA methods as a tool for inter-laboratory surveillance","year":2013,"lang":"en","type":"review","venue":"Eurosurveillance","topic":"Salmonella and Campylobacter epidemiology","field":"Agricultural and Biological Sciences","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada","funders":"National Institutes of Health","keywords":"Multiple Loci VNTR Analysis; Subtyping; Variable number tandem repeat; Computer science; Biodefense; Computational biology; Biology; Genetics; Microbiology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001612175,0.000365215,0.001482653,0.00002154321,0.00008763796,0.00002969083,0.0003733565,0.0002778224,0.00003134935],"category_scores_gemma":[0.0004872585,0.0001498877,0.0001922988,0.0003076206,0.00009767797,0.00004175097,0.0001313657,0.0001489184,0.00004117389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003226808,"about_ca_system_score_gemma":0.00004200824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002686498,"about_ca_topic_score_gemma":0.00004185319,"domain_scores_codex":[0.9973437,0.0007302826,0.0008694254,0.0006422959,0.0000966974,0.0003176167],"domain_scores_gemma":[0.9968297,0.002053354,0.0007236379,0.000159622,0.0001511693,0.00008249407],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006484328,0.0000193141,0.0008542648,0.001105316,0.00003332944,2.883868e-7,0.00001583819,3.43769e-8,0.0006967165,0.00009391639,0.0002678168,0.9969067],"study_design_scores_gemma":[0.00005690056,0.0000801131,0.004401839,0.0002379619,0.00001526692,0.000009594362,0.000006497857,0.000005984939,0.0000437668,0.00006033262,0.9947689,0.0003127959],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00608373,0.9910476,0.0009209872,0.00004245805,0.0002458004,0.001301634,0.0001899116,0.0000637932,0.0001040692],"genre_scores_gemma":[0.0004028367,0.9883637,0.009735109,0.0001132876,0.0002372189,0.0006393535,0.0003156486,0.000006892269,0.0001859744],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9965939,"threshold_uncertainty_score":0.6112244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06050973823234124,"score_gpt":0.3564640458542983,"score_spread":0.295954307621957,"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."}}