{"id":"W4388494625","doi":"10.3390/bs13110912","title":"The Mental Health Impacts of a Pandemic: A Multiaxial Conceptual Model for COVID-19","year":2023,"lang":"en","type":"article","venue":"Behavioral Sciences","topic":"COVID-19 and Mental Health","field":"Psychology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; University of Alberta","keywords":"Pandemic; Mental health; Psychology; Vulnerability (computing); Context (archaeology); Coronavirus disease 2019 (COVID-19); Conceptual model; Population; Public health; Social psychology; Environmental health; Psychiatry; Geography; Medicine; Computer security; Computer science; Disease; Nursing","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001617896,0.0001112303,0.0001787834,0.00008043415,0.0009601453,0.00002505108,0.0003702628,0.00005572121,0.00004395689],"category_scores_gemma":[0.00005304025,0.00007329194,0.00009198161,0.0004257369,0.0009636245,0.00008082674,0.00007545576,0.00007744932,0.00002171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000292952,"about_ca_system_score_gemma":0.001819317,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01237682,"about_ca_topic_score_gemma":0.007493809,"domain_scores_codex":[0.998278,0.00009447274,0.000331603,0.0003269597,0.0003279975,0.0006409611],"domain_scores_gemma":[0.9990249,0.0002652058,0.0001757464,0.0001654668,0.00002180886,0.0003469089],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.001697757,0.001455595,0.4341647,0.0002013178,0.00003588635,0.000009887693,0.2518616,0.0008020743,0.005230878,0.03686571,0.1371044,0.1305702],"study_design_scores_gemma":[0.02698496,0.02280346,0.2202908,0.000226813,0.0001517419,0.0001272141,0.326686,0.1147796,0.0009340761,0.01012875,0.274482,0.002404477],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924152,0.0003251177,0.0003299081,0.004607246,0.0007769647,0.001015945,0.0003676566,0.0001022219,0.00005971398],"genre_scores_gemma":[0.9973006,0.00007787655,0.0001401104,0.001488504,0.00004996994,0.0001334551,0.00002418349,0.000007751627,0.0007774952],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2138739,"threshold_uncertainty_score":0.9941999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.413675437142717,"score_gpt":0.5726940792224241,"score_spread":0.1590186420797071,"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."}}