{"id":"W4389365579","doi":"10.53854/liim-3104-2","title":"Synergistic fight against future pandemics: Lessons from previous pandemics","year":2023,"lang":"en","type":"review","venue":"Infezioni in Medicina","topic":"Zoonotic diseases and public health","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ambrose University","funders":"","keywords":"Pandemic; Preparedness; Public health; Economic growth; Health care; Population; Global health; Urbanization; Development economics; Business; Political science; Environmental planning; Geography; Disease; Infectious disease (medical specialty); Environmental health; Medicine; Economics; Coronavirus disease 2019 (COVID-19)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0133446,0.00184321,0.00167745,0.001298825,0.004190856,0.007737863,0.003343908,0.009465891,0.01023709],"category_scores_gemma":[0.01476716,0.000536809,0.001859618,0.0008940661,0.007955591,0.01752575,0.008367066,0.01505045,0.003677899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002875727,"about_ca_system_score_gemma":0.01610438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004136002,"about_ca_topic_score_gemma":0.009917565,"domain_scores_codex":[0.9945128,0.002734466,0.0002631644,0.0005063462,0.001009047,0.0009741657],"domain_scores_gemma":[0.9858288,0.005601543,0.0006433635,0.0009043871,0.002993751,0.004028188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002755081,0.0005963047,0.003029434,0.005446307,0.0003254931,0.001663868,0.009572593,0.002797884,0.001508825,0.07696145,0.512802,0.3850203],"study_design_scores_gemma":[0.00008519449,0.0004367909,0.001306876,0.004913225,0.000141112,0.0008292692,0.01144728,0.0006613869,0.0007541054,0.1342991,0.8450001,0.000125657],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"review","genre_scores_codex":[0.003987967,0.1531578,0.007040642,0.783532,0.02214171,0.0001219624,0.0002083469,0.0002549542,0.02955463],"genre_scores_gemma":[0.1479611,0.3596538,0.02864305,0.4235513,0.02060841,0.0004192991,0.0004620572,0.0002764751,0.01842449],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.0133446,"threshold_uncertainty_score":0.07057387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09071663958084217,"score_gpt":0.4096782765698499,"score_spread":0.3189616369890077,"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."}}