{"id":"W2883375453","doi":"10.14745/ccdr.v41i09a02","title":"Big Data and the Global Public Health Intelligence Network (GPHIN)","year":2015,"lang":"en","type":"article","venue":"Canada Communicable Disease Report","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":110,"is_retracted":false,"has_abstract":true,"ca_institutions":"Response Biomedical (Canada); Public Health Agency of Canada; Western University","funders":"Public Health Agency; Public Health Agency of Canada","keywords":"Public health; Outbreak; Big data; Emerging infectious disease; Global health; Infectious disease (medical specialty); International Health Regulations; Situation awareness; Environmental health; Globalization; Capacity building; Public health surveillance; Social media; Business; Disease; Medicine; Political science; Computer science; Coronavirus disease 2019 (COVID-19); Economic growth; Engineering; Virology; Data mining; Pathology; Economics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.01403452,0.0007392653,0.0005167188,0.004044478,0.00160882,0.008714308,0.001405073,0.003071184,0.005202116],"category_scores_gemma":[0.02580303,0.0003201456,0.0005650532,0.006545932,0.003611885,0.01197926,0.007096741,0.003159305,0.001143238],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002761252,"about_ca_system_score_gemma":0.005017492,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003193007,"about_ca_topic_score_gemma":0.001741033,"domain_scores_codex":[0.9932167,0.00369043,0.0003935492,0.0006517093,0.001647958,0.0003997288],"domain_scores_gemma":[0.959294,0.02489307,0.003553608,0.003691149,0.005095879,0.003472232],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001517215,0.00006022808,0.01407213,0.00114019,0.0001490558,0.0002530766,0.001043008,0.004713527,0.000434606,0.3474026,0.2852148,0.3453651],"study_design_scores_gemma":[0.00003130597,0.00007909748,0.007230389,0.001603414,0.00004194218,0.000278408,0.001479032,0.009332039,0.0006251975,0.2705336,0.7086806,0.00008500614],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01993564,0.07565538,0.060334,0.6287487,0.01400483,0.0004918989,0.008266644,0.00226001,0.190303],"genre_scores_gemma":[0.5607949,0.1340733,0.142453,0.0956569,0.02258745,0.001369539,0.01511953,0.0007642346,0.02718111],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9972388,"threshold_uncertainty_score":0.07422256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1688642691876727,"score_gpt":0.3365549164026105,"score_spread":0.1676906472149378,"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."}}