{"id":"W2915883351","doi":"10.2196/11615","title":"Social Media Surveillance for Outbreak Projection via Transmission Models: Longitudinal Observational Study","year":2019,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Data mining; Data quality; Machine learning; Metric (unit); Projection (relational algebra); Leverage (statistics); Artificial intelligence; Algorithm","routes":{"ca_aff":true,"ca_fund":false,"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":[0.01196144,0.0008168856,0.0005969799,0.001447493,0.0007183545,0.001118665,0.001115429,0.0008584526,0.002329448],"category_scores_gemma":[0.03571563,0.0005853064,0.001521493,0.001594806,0.0004296946,0.001370434,0.001495066,0.001803716,0.0007018773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006672585,"about_ca_system_score_gemma":0.00129663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01463475,"about_ca_topic_score_gemma":0.01161035,"domain_scores_codex":[0.994783,0.003643489,0.0003155413,0.0006714892,0.000319435,0.0002669901],"domain_scores_gemma":[0.9798877,0.01110846,0.004098464,0.003122437,0.00117897,0.0006039042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003839168,0.0005461577,0.9819873,0.00009040633,0.0006394116,0.0001613399,0.0003595471,0.004979272,0.0001204697,0.0007421612,0.001837553,0.00815252],"study_design_scores_gemma":[0.0001414383,0.001336548,0.6177999,0.0002720448,0.0008059615,0.0007200298,0.002300565,0.3690187,0.0006202769,0.00380099,0.003088688,0.0000948767],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.978977,0.0004975164,0.01512101,0.0004293355,0.0000393272,0.0002036424,0.004052542,0.00007046344,0.0006092458],"genre_scores_gemma":[0.9914626,0.0001932465,0.004262497,0.00006760863,0.00004486345,0.0002018517,0.003551431,0.00001150131,0.0002043242],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01463475,"threshold_uncertainty_score":0.06325895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1396317710019518,"score_gpt":0.3708583158334395,"score_spread":0.2312265448314877,"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."}}