{"id":"W4312103270","doi":"10.1093/geroni/igac059.1884","title":"COMMUNITY MOBILITY PATTERNS OF OLDER ADULTS DURING THE COVID-19 PANDEMIC","year":2022,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Baycrest Hospital; Lakehead University; University of Ottawa","funders":"","keywords":"Pandemic; Anxiety; Coronavirus disease 2019 (COVID-19); Gerontology; Public health; TRIPS architecture; Medicine; Scale (ratio); Psychology; Demography; Geography; Psychiatry; Sociology; Nursing; Disease; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004663666,0.0001752847,0.0002317359,0.0007294762,0.0006402825,0.0005695194,0.0003059145,0.0004846118,0.001374204],"category_scores_gemma":[0.002169428,0.0001364065,0.0003695695,0.0006338466,0.0001326376,0.0005234496,0.0007176977,0.0004795941,0.0001643048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004432115,"about_ca_system_score_gemma":0.0004076911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0402878,"about_ca_topic_score_gemma":0.0754959,"domain_scores_codex":[0.999693,0.000063321,0.00004452572,0.00005303711,0.00005507629,0.00009096154],"domain_scores_gemma":[0.9992123,0.00004963451,0.000335581,0.00002865178,0.0001595497,0.0002143312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006980156,0.00004754668,0.997003,0.00001485056,0.00003078437,0.00003292705,0.0006288381,0.00002125851,0.0001248171,0.000009693682,0.0001788833,0.001837456],"study_design_scores_gemma":[0.000002407234,0.00006572349,0.9984138,0.0000115982,0.000005968783,0.00003604473,0.001263998,0.00005320862,0.00001200776,0.000007815259,0.0001239434,0.000003581015],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987935,0.0001521114,0.00002814425,0.00007099479,0.000006158586,0.00001980388,0.0005371634,0.000001907717,0.0003902093],"genre_scores_gemma":[0.9993182,0.0000705434,0.00003834753,0.0000336813,0.000005219753,0.00001660686,0.0003704011,6.241757e-7,0.0001462572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0402878,"threshold_uncertainty_score":0.08010656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07029283845906568,"score_gpt":0.3867509069459145,"score_spread":0.3164580684868488,"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."}}