{"id":"W4406016592","doi":"10.1038/s41598-024-81519-3","title":"Understanding the interplay between social isolation, age, and loneliness during the COVID-19 pandemic","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; École de Technologie Supérieure; Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada; Canadian Institutes of Health Research","keywords":"Loneliness; Pandemic; Coronavirus disease 2019 (COVID-19); Social isolation; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Isolation (microbiology); Betacoronavirus; Virology; Coronavirus Infections; Data science; Medicine; Biology; Computer science; Bioinformatics; Outbreak; Psychiatry; Pathology; Disease; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001125407,0.000248068,0.0003699987,0.0009083417,0.002108574,0.00180607,0.0005884688,0.0003914002,0.001503307],"category_scores_gemma":[0.003596814,0.0001686637,0.0004996027,0.00124239,0.0008536629,0.001380638,0.001514566,0.0006698914,0.00009213875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005459795,"about_ca_system_score_gemma":0.009956205,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8464652,"about_ca_topic_score_gemma":0.9151391,"domain_scores_codex":[0.9993305,0.000117667,0.00002402891,0.00008624498,0.0001156016,0.0003260236],"domain_scores_gemma":[0.9989585,0.0001920104,0.0002449798,0.00004465395,0.0002437261,0.0003161097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001186983,0.00004225849,0.9528667,0.000116967,0.00009771297,0.00009549807,0.01695978,0.0003383725,0.0002326332,0.0007390488,0.001084954,0.02730745],"study_design_scores_gemma":[7.983934e-7,0.00001457527,0.9897139,0.00004422421,0.00001466221,0.00001644126,0.009110617,0.0002053175,0.00001706345,0.0001285182,0.0007257922,0.000008044783],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994293,0.00112672,0.0002153536,0.001072332,0.00001481336,0.00002375902,0.0006593736,0.000004868978,0.002589813],"genre_scores_gemma":[0.9985222,0.0007088091,0.000151809,0.00007992694,0.000008696709,0.00001357579,0.0002503972,0.000001770577,0.0002628415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8464652,"threshold_uncertainty_score":0.308878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.129793044513412,"score_gpt":0.4194427300580339,"score_spread":0.2896496855446219,"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."}}