{"id":"W3185616445","doi":"10.1016/j.ajo.2021.07.024","title":"Disparities in Eye Care Utilization During the COVID-19 Pandemic","year":2021,"lang":"en","type":"article","venue":"American Journal of Ophthalmology","topic":"Ophthalmology and Visual Impairment Studies","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"National Eye Institute; Research to Prevent Blindness","keywords":"Medicine; Odds; Odds ratio; Multinomial logistic regression; Telemedicine; Pandemic; Logistic regression; Demography; Socioeconomic status; Coronavirus disease 2019 (COVID-19); Health care; Internal medicine; Population; Environmental health","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":[0.0002810366,0.0001278748,0.0005015672,0.0001403843,0.0001354248,0.00000725735,0.0001088166,0.00006061447,0.0002186247],"category_scores_gemma":[0.0006942377,0.00008890647,0.000116091,0.0003681268,0.0005998636,0.00006334144,0.00007284575,0.0003887983,0.000003988474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001925466,"about_ca_system_score_gemma":0.0003190275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009146673,"about_ca_topic_score_gemma":0.00000387644,"domain_scores_codex":[0.9986558,0.0003568942,0.0004169415,0.0001535012,0.0001577042,0.0002591841],"domain_scores_gemma":[0.9989353,0.000273923,0.0002951045,0.0001663964,0.0001980104,0.0001312778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000468093,0.0001617785,0.9908898,0.00008828203,0.0001082934,0.006174124,0.001332167,0.00004596925,0.0003620189,0.00003533181,0.00004010649,0.0002940742],"study_design_scores_gemma":[0.001046529,0.001614763,0.8753242,0.00004130319,0.00006287186,0.1125423,0.008919224,0.000002895308,0.00009342791,0.00009919961,0.0001801849,0.00007302911],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933537,0.002657561,0.00002148825,0.00309025,0.0002300007,0.00008939614,0.000003453805,0.000007521804,0.0005466413],"genre_scores_gemma":[0.9983956,0.0003111559,0.0001170389,0.0006748295,0.0001156919,0.000006245918,0.000004892577,0.00001201664,0.0003625782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1155655,"threshold_uncertainty_score":0.3625501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07667251738311773,"score_gpt":0.414537289911616,"score_spread":0.3378647725284983,"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."}}