{"id":"W2884434207","doi":"10.3389/fvets.2018.00160","title":"Multi-Target Strategy for Pan/Foot-and-Mouth Disease Virus (FMDV) Detection: A Combination of Sequences Analysis, in Silico Predictions and Laboratory Diagnostic Evaluation","year":2018,"lang":"en","type":"article","venue":"Frontiers in Veterinary Science","topic":"Animal Disease Management and Epidemiology","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint John Regional Hospital; Dalhousie University; University of New Brunswick","funders":"Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria","keywords":"Foot-and-mouth disease virus; Virology; In silico; Foot-and-mouth disease; Biology; Primer (cosmetics); Polymerase chain reaction; Disease; Virus; Gold standard (test); Viral load; Computational biology; Medicine; Genetics; Gene; Pathology; Internal medicine","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":[0.002162294,0.001692436,0.001608005,0.001120742,0.0002581885,0.001148615,0.0009223203,0.001305264,0.0007575863],"category_scores_gemma":[0.001600901,0.0007690107,0.001515863,0.0004893421,0.0004160489,0.0007724373,0.0006462756,0.001120294,0.0009673937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004684243,"about_ca_system_score_gemma":0.0005181733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003664463,"about_ca_topic_score_gemma":0.0007527744,"domain_scores_codex":[0.998206,0.0003434923,0.0001192559,0.0005581396,0.0006542496,0.000118843],"domain_scores_gemma":[0.9991958,0.0003408553,0.0001811582,0.00006460459,0.0001705777,0.00004704196],"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":[0.0002748665,0.0002634833,0.00184975,0.0003767151,0.0000845391,0.0001484446,0.00006261943,0.007572236,0.9685592,0.0002421983,0.0001305181,0.02043538],"study_design_scores_gemma":[0.00002689703,0.001042953,0.002007382,0.0000253396,0.000146646,0.0003939976,0.00004704783,0.08539203,0.9086082,0.0002232501,0.002013745,0.00007255532],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5082778,0.00297807,0.4817028,0.0002713545,0.0001935512,0.001012454,0.001040649,0.00244928,0.002074093],"genre_scores_gemma":[0.4680988,0.001362591,0.5264355,0.0002051242,0.00003496317,0.0005923599,0.001409334,0.0002004369,0.001660903],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002162294,"threshold_uncertainty_score":0.01143545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04922757310309449,"score_gpt":0.3080191166458443,"score_spread":0.2587915435427498,"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."}}