{"id":"W3024150663","doi":"10.2196/19332","title":"COVID-19 Crisis in Jordan: Response, Scenarios, Strategies, and Recommendations","year":2020,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Viral Infections and Outbreaks Research","field":"Medicine","cited_by":98,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Public health; Contact tracing; Government (linguistics); Health care; Social distance; Communicable disease; Business; International Health Regulations; Environmental health; Public relations; Medicine; Disease; Political science; Economic growth; Infectious disease (medical specialty); Economics; Coronavirus disease 2019 (COVID-19); Nursing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039718,0.001590853,0.0007827224,0.002956504,0.00415883,0.009084431,0.003075392,0.008241116,0.01481931],"category_scores_gemma":[0.004422088,0.000310114,0.001103792,0.001796041,0.001829599,0.006892066,0.00596711,0.006098851,0.002434484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007628564,"about_ca_system_score_gemma":0.02660922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01605495,"about_ca_topic_score_gemma":0.03127091,"domain_scores_codex":[0.9974318,0.0009882695,0.0001742221,0.0001659909,0.000349236,0.0008904801],"domain_scores_gemma":[0.995209,0.0006296216,0.0003582316,0.00005678413,0.001415324,0.002330869],"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":[0.0003260642,0.0009290198,0.02035935,0.006476468,0.0001204359,0.008468762,0.007378267,0.004336332,0.0008247222,0.03501735,0.7576047,0.1581586],"study_design_scores_gemma":[0.0001103243,0.0004531844,0.01693483,0.01658827,0.0001164108,0.004212481,0.2691626,0.006377677,0.0009600084,0.04522523,0.6395502,0.0003088016],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02144733,0.06859572,0.002241386,0.8491015,0.008967965,0.0007031421,0.002086102,0.0005200923,0.04633668],"genre_scores_gemma":[0.4363997,0.2685748,0.02493101,0.1921215,0.006965016,0.002701075,0.006923423,0.0001804863,0.06120302],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01605495,"threshold_uncertainty_score":0.05534935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08953010166876323,"score_gpt":0.4047164781099715,"score_spread":0.3151863764412082,"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."}}