{"id":"W4210705111","doi":"10.1891/1062-8061.30.168","title":"Pandemic, Creating a Usable Past: Epidemic History, COVID-19, and the Future of Health and Pandemic Histories","year":2022,"lang":"en","type":"article","venue":"Nursing History Review","topic":"Historical Studies and Socio-cultural Analysis","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); USable; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); History; Virology; Outbreak; Computer science; Medicine; Infectious disease (medical specialty); World Wide Web; Disease","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":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00180187,0.0002380467,0.001114859,0.00005453981,0.004237296,0.000009773823,0.0002021537,0.00003578088,0.001266015],"category_scores_gemma":[0.0001971101,0.0001604977,0.0002367406,0.00006583846,0.001569604,0.00009769137,0.00007610389,0.0004010381,0.000001648548],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0212712,"about_ca_system_score_gemma":0.0003137992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001650028,"about_ca_topic_score_gemma":0.0004145253,"domain_scores_codex":[0.9974394,0.0008379131,0.0007361736,0.0003655763,0.000332951,0.0002880188],"domain_scores_gemma":[0.9984574,0.0003118251,0.0007199271,0.0002378633,0.00007990709,0.0001930336],"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":[0.00004358854,0.00004648535,0.0007576079,0.002004125,0.00006988374,0.000001323441,0.3081183,0.000001214895,0.000001627013,0.03603264,0.6230932,0.02982996],"study_design_scores_gemma":[0.0004044743,0.00009124995,0.000008556251,0.0003541271,0.0002393842,0.00001838281,0.01127792,0.00001136715,3.756081e-9,0.0009142992,0.986495,0.0001852617],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001122781,0.9486418,0.00001276469,0.04654259,0.001190793,0.0003707299,0.00001046117,0.00006753927,0.002040545],"genre_scores_gemma":[0.02748551,0.8844799,0.0001303237,0.03300114,0.00128283,0.0003326842,0.00005202684,0.00006370726,0.05317182],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.3634018,"threshold_uncertainty_score":0.999647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09272493756000821,"score_gpt":0.2917745490388689,"score_spread":0.1990496114788607,"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."}}