{"id":"W1945721908","doi":"10.1007/bf03405213","title":"The Global Public Health Intelligence Network and early warning outbreak detection: a Canadian contribution to global public health.","year":2006,"lang":"en","type":"article","venue":"PubMed","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":189,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Public health; Outbreak; Global health; Warning system; Credibility; Infectious disease (medical specialty); International Health Regulations; Global network; The Internet; Public health surveillance; Political science; Public relations; Environmental health; Medicine; Disease; Coronavirus disease 2019 (COVID-19); Computer science; Telecommunications; Virology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.01447021,0.000749689,0.0005534414,0.006055892,0.00270787,0.003990661,0.001874238,0.00195483,0.01616223],"category_scores_gemma":[0.04441724,0.0004189768,0.0005523596,0.00655909,0.002557525,0.00303517,0.002788913,0.003485507,0.001374735],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02179229,"about_ca_system_score_gemma":0.1334638,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9450096,"about_ca_topic_score_gemma":0.9472779,"domain_scores_codex":[0.993982,0.002104786,0.0003409684,0.0002269781,0.002682816,0.00066243],"domain_scores_gemma":[0.9504631,0.01170151,0.001657857,0.001999805,0.02904988,0.005127747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001805482,0.0001133801,0.02337923,0.001087092,0.0001413003,0.0002137361,0.001015104,0.0007260039,0.0003872457,0.02549208,0.5409808,0.4062834],"study_design_scores_gemma":[0.0001281504,0.0001057357,0.07074081,0.002030214,0.0002798047,0.0002508746,0.002769319,0.0009455007,0.0006738462,0.01025257,0.9117345,0.00008867458],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.008861838,0.1450301,0.006938262,0.6276786,0.01572838,0.000541448,0.01157378,0.0004769958,0.1831706],"genre_scores_gemma":[0.3584482,0.3642875,0.05230365,0.07376839,0.01930964,0.0007596073,0.01131046,0.0004633946,0.1193491],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9782077,"threshold_uncertainty_score":0.1581149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07573348898766227,"score_gpt":0.3318292591236327,"score_spread":0.2560957701359704,"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."}}