{"id":"W4384499913","doi":"10.1080/20479700.2023.2235786","title":"Using visualization technique to communicate the conceptual structure of SARS-CoV-2 to multidisciplinary audience and lessons from the pandemic for future preparedness","year":2023,"lang":"en","type":"article","venue":"International Journal of Healthcare Management","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Pandemic; Multidisciplinary approach; Misinformation; Visualization; Preparedness; Coronavirus disease 2019 (COVID-19); Public health; Conceptual framework; Data science; Psychology; Sociology; Computer science; Medicine; Political science; Infectious disease (medical specialty); Social science; Disease; Nursing","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":[0.0009059661,0.0000639915,0.0001045609,0.0001176859,0.0003307785,0.00006606978,0.0006446986,0.0000384413,0.000004813815],"category_scores_gemma":[0.0001455033,0.00004044465,0.00003828706,0.0002616328,0.00009420941,0.0002028018,0.0002337359,0.00009110748,7.28451e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001575941,"about_ca_system_score_gemma":0.0001036636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006964062,"about_ca_topic_score_gemma":0.002006904,"domain_scores_codex":[0.9988022,0.0001593426,0.0003507985,0.00007426256,0.0004859827,0.0001273745],"domain_scores_gemma":[0.9989017,0.0001782818,0.0003093467,0.0001241028,0.0004333493,0.00005325958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004739137,0.00004937657,0.002641668,0.00007011012,0.0002765555,0.000005926239,0.7285306,0.002615013,0.006698133,0.1750455,0.009634811,0.07395832],"study_design_scores_gemma":[0.001243903,0.0003307305,0.05105755,0.001142196,0.00007767929,0.00001996798,0.7788002,0.003140216,0.002538652,0.01619942,0.1451207,0.0003288187],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9035153,0.0001121352,0.02329771,0.07090337,0.0008524827,0.001043814,0.0001443157,0.00002009123,0.0001107752],"genre_scores_gemma":[0.995654,0.0003491947,0.002056785,0.00168779,0.0002147118,0.000005418593,0.000009381756,0.000005169909,0.0000175509],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1588461,"threshold_uncertainty_score":0.2544114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1783230263310619,"score_gpt":0.5023145504969991,"score_spread":0.3239915241659372,"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."}}