{"id":"W2782762456","doi":"","title":"Human health in a modern world: can technology solve the mismatch?","year":2017,"lang":"en","type":"article","venue":"Computer Science and Software Engineering","topic":"Global Public Health Policies and Epidemiology","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Life expectancy; Pandemic; SAFER; China; Developing country; Medicine; Health care; Disease; Globe; Chronic disease; Developed country; Global health; Population; Development economics; Economic growth; Environmental health; Intensive care medicine; Coronavirus disease 2019 (COVID-19); Computer science; Political science; Computer security; Economics; Pathology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.001407154,0.0001121546,0.0001995334,0.0004289088,0.001036282,0.0004178156,0.0007940186,0.00003656455,0.000001322122],"category_scores_gemma":[0.0003971869,0.0000847426,0.00001736361,0.0004724228,0.0002707716,0.0005000666,0.000653855,0.0001857133,0.000003555806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006003183,"about_ca_system_score_gemma":0.00006778457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002678758,"about_ca_topic_score_gemma":0.0008455613,"domain_scores_codex":[0.9988113,0.000003608006,0.0002095429,0.0002672358,0.0001180261,0.0005903025],"domain_scores_gemma":[0.9993243,0.00003206704,0.0001225867,0.0004138983,0.00007341925,0.00003376911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003329072,0.00007222722,0.1161033,0.0005648659,0.00001851586,0.00002724595,0.0008200096,0.05335076,0.00006394069,0.2731665,0.08316302,0.4726463],"study_design_scores_gemma":[0.0002905383,0.00001587235,0.1863734,0.0001284224,0.000002312211,0.000008789852,0.00004471193,0.6693317,0.000001175293,0.006520847,0.1370347,0.0002474128],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6172664,0.0004380226,0.1350251,0.2441193,0.001743424,0.0005265854,0.000002232178,0.0004811008,0.0003977198],"genre_scores_gemma":[0.9781453,0.000009394288,0.004351827,0.01692385,0.0005272962,0.0000145765,9.412673e-7,0.000009963622,0.0000168654],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.615981,"threshold_uncertainty_score":0.797035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02306594858893938,"score_gpt":0.2829002037322391,"score_spread":0.2598342551432997,"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."}}