{"id":"W3134265538","doi":"10.1371/journal.pone.0247997","title":"Predicting fear and perceived health during the COVID-19 pandemic using machine learning: A cross-national longitudinal study","year":2021,"lang":"en","type":"article","venue":"PLoS ONE","topic":"COVID-19 and Mental Health","field":"Psychology","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Homewood Research Institute","funders":"Foundation for Research in Science and the Humanities; Baugarten Stiftung; European Commission; Universität Zürich; H2020 Marie Skłodowska-Curie Actions; Universität Wien; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Pandemic; Anxiety; Vulnerability (computing); Psychology; Environmental health; Longitudinal study; Medicine; Disease; Clinical psychology; Coronavirus disease 2019 (COVID-19); Psychiatry; Computer security; Infectious disease (medical specialty)","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":[0.004370239,0.00031277,0.0004038407,0.0003652563,0.0007210569,0.0009749844,0.0004807516,0.0008432986,0.001207097],"category_scores_gemma":[0.006285299,0.0003978812,0.0009653746,0.0004085585,0.0003775012,0.0006785923,0.0008424753,0.00180471,0.0003293602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003832956,"about_ca_system_score_gemma":0.0006051735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01474556,"about_ca_topic_score_gemma":0.01449997,"domain_scores_codex":[0.9991546,0.0004481539,0.00005644678,0.0001282269,0.0000740777,0.0001385611],"domain_scores_gemma":[0.995948,0.001614612,0.0007698977,0.0006768826,0.0004099246,0.0005806618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001564278,0.0004926712,0.9963263,0.000006902056,0.0001163746,0.00002591431,0.0004693546,0.0001766644,0.0001336957,0.00002674761,0.0001060272,0.001962801],"study_design_scores_gemma":[0.000009226345,0.0004838544,0.9954378,0.00001444454,0.00005286003,0.00005442119,0.0009617805,0.002626219,0.00008376304,0.00005851708,0.0002062408,0.00001085162],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996408,0.00003014423,0.000132208,0.00003630991,0.000003660361,0.000005703485,0.00007409001,0.000001377709,0.00007568068],"genre_scores_gemma":[0.9993206,0.00004647484,0.0001656175,0.00002862495,0.000004861516,0.00001935299,0.000237673,0.000001667218,0.0001751205],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01474556,"threshold_uncertainty_score":0.02931947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3018490715727615,"score_gpt":0.4624450572718053,"score_spread":0.1605959856990439,"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."}}