{"id":"W3174733134","doi":"10.1111/tbed.14195","title":"DTU‐DADS‐Aqua: A simulation framework for modelling waterborne spread of highly infectious pathogens in marine aquaculture","year":2021,"lang":"en","type":"article","venue":"Transboundary and Emerging Diseases","topic":"Animal Disease Management and Epidemiology","field":"Agricultural and Biological Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; University of Prince Edward Island","funders":"Canada First Research Excellence Fund; Ocean Frontier Institute; Canada Excellence Research Chairs, Government of Canada","keywords":"Salmo; Outbreak; Culling; Simulation modeling; Population; Transmission (telecommunications); Aquaculture; Environmental science; Fishery; Biology; Ecology; Computer science; Fish <Actinopterygii>; Environmental health; Virology; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001360526,0.001267721,0.0008706744,0.0009127676,0.0008067502,0.00136655,0.002472284,0.001626511,0.005871241],"category_scores_gemma":[0.003313845,0.0009616007,0.002065685,0.000723958,0.000678841,0.00120421,0.001742451,0.001514407,0.000692744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001730575,"about_ca_system_score_gemma":0.002642006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05413414,"about_ca_topic_score_gemma":0.03666279,"domain_scores_codex":[0.9995453,0.0002090816,0.00004868138,0.00006558084,0.00007556202,0.00005581172],"domain_scores_gemma":[0.998687,0.0007579993,0.000136317,0.00008071639,0.0001996148,0.0001383203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002864529,0.00002111684,0.001002347,0.00003965487,0.00004053264,0.00003404306,0.00003622009,0.9905844,0.0003766601,0.004621011,0.0007799704,0.002435368],"study_design_scores_gemma":[0.0000164587,0.00001012244,0.0001015607,0.000007405961,0.000008712584,0.000008932348,0.000009137478,0.9960135,0.0001175401,0.001531724,0.002166488,0.000008392213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08044166,0.0006245294,0.8862228,0.0008236483,0.0002550519,0.0004309731,0.008543903,0.008761184,0.01389626],"genre_scores_gemma":[0.5978401,0.001121545,0.3845762,0.000259109,0.0000897697,0.001501417,0.007368201,0.001222122,0.006021521],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05413414,"threshold_uncertainty_score":0.1076381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02675107631967003,"score_gpt":0.2624066919935862,"score_spread":0.2356556156739162,"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."}}