{"id":"W4396502155","doi":"10.14745/ccdr.v50i34a02","title":"Innovations in public health surveillance: An overview of novel use of data and analytic methods","year":2024,"lang":"en","type":"article","venue":"Canada Communicable Disease Report","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Public Health Agency of Canada","funders":"Public Health Agency; Public Health Agency of Canada","keywords":"Public health; Disease surveillance; Public health surveillance; Data governance; Big data; Business; Computer science; Data science; Data quality; Medicine; Marketing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002785527,0.0001667919,0.0007495221,0.0002645017,0.00004977192,0.00003908621,0.0004682703,0.00003471525,0.00004176221],"category_scores_gemma":[0.002641905,0.0001635327,0.00004010833,0.001768513,0.0001724561,0.0005078997,0.0005948011,0.0002305605,1.072698e-7],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002649351,"about_ca_system_score_gemma":0.01396466,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2836763,"about_ca_topic_score_gemma":0.4187199,"domain_scores_codex":[0.9973188,0.0003947135,0.001092844,0.0004562828,0.0004474443,0.000289932],"domain_scores_gemma":[0.9938852,0.0004778284,0.0003201923,0.004350061,0.0003981478,0.0005685636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001232711,0.001215258,0.9282871,0.006424997,0.0006264693,0.001505686,0.0001069113,0.00009651235,0.0002655223,0.003867545,0.01670081,0.0407799],"study_design_scores_gemma":[0.0005368619,0.00003614145,0.7651306,0.0007417427,0.00007194593,0.0001202225,0.0001139822,0.03691468,0.000003550033,0.00004100333,0.1960981,0.000191189],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.807272,0.1441883,0.004033057,0.0153815,0.000445139,0.00217121,0.02538187,0.0002424393,0.000884519],"genre_scores_gemma":[0.9764811,0.002450929,0.0120191,0.0005355799,0.00001460502,0.0000151326,0.008363992,0.0000346931,0.00008490193],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1793973,"threshold_uncertainty_score":0.9916252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4229131117574185,"score_gpt":0.4821898982799535,"score_spread":0.05927678652253493,"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."}}