{"id":"W2007750837","doi":"10.1016/j.ypmed.2013.04.011","title":"Influenza H3N2 variant viruses with pandemic potential: Preventing catastrophe in remote and isolated Canadian communities","year":2013,"lang":"en","type":"article","venue":"Preventive Medicine","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; York University","funders":"Canadian Institutes of Health Research; Compute Canada","keywords":"Pandemic; Medicine; Outbreak; Vaccination; Population; Demography; Epidemiology; Transmission (telecommunications); Environmental health; Census; Coronavirus disease 2019 (COVID-19); Virology; Disease; Infectious disease (medical specialty)","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":[0.001022285,0.0005300753,0.0004047139,0.001078875,0.007818441,0.001318129,0.001492624,0.000898511,0.002509388],"category_scores_gemma":[0.003612756,0.0002707591,0.0005579362,0.002342119,0.00134072,0.000868527,0.001563436,0.001296709,0.0001304757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03010666,"about_ca_system_score_gemma":0.05643856,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9923525,"about_ca_topic_score_gemma":0.9968669,"domain_scores_codex":[0.9986321,0.0001653383,0.00003851589,0.00007966573,0.0002306794,0.0008535453],"domain_scores_gemma":[0.9976789,0.000153421,0.0003754246,0.00004192678,0.0007650822,0.0009851555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008348293,0.0008288317,0.9260353,0.000533502,0.0001376608,0.0008922591,0.01901542,0.0004705194,0.0007106424,0.001144006,0.007518375,0.04187852],"study_design_scores_gemma":[0.00003892947,0.0001569777,0.9638814,0.0001579001,0.0000555619,0.0001188064,0.03228484,0.0002091203,0.0001168209,0.0001520788,0.002793867,0.00003369013],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911129,0.001584145,0.00008053294,0.001645651,0.0000335223,0.00009737668,0.0005632467,0.00000585284,0.004876742],"genre_scores_gemma":[0.9974698,0.001126945,0.0001592997,0.0002792363,0.00001756662,0.00002645402,0.000195512,0.000001767083,0.000723492],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03010666,"threshold_uncertainty_score":0.2184401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06662016399070957,"score_gpt":0.3466805856077469,"score_spread":0.2800604216170373,"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."}}