{"id":"W4408889694","doi":"10.14336/ad.2024.1744","title":"Association Between Dementia and Optical Coherence Tomography Scan Quality","year":2025,"lang":"en","type":"article","venue":"Aging and Disease","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Medical Research Council; National Research Foundation Singapore; Agency for Science, Technology and Research; Nanyang Technological University; Singapore Eye Research Institute; National Research Foundation; Medical Research Council; Duke-NUS Medical School","keywords":"Dementia; Optical coherence tomography; Medicine; Association (psychology); Computed tomography; Tomography; Internal medicine; Radiology; Psychology; Disease","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001955938,0.00008173097,0.00009552644,0.00007153197,0.000122393,0.00007395569,0.00005135347,0.00003489642,0.000008337468],"category_scores_gemma":[0.000102007,0.00008774343,0.00003033181,0.0002506607,0.00004946926,0.0000722959,0.0000279502,0.0001210711,0.000002505465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001575271,"about_ca_system_score_gemma":0.00001440792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001948037,"about_ca_topic_score_gemma":0.000006541175,"domain_scores_codex":[0.9994423,0.000031191,0.0001293902,0.0001538009,0.0000898853,0.0001533869],"domain_scores_gemma":[0.9993955,0.0002180135,0.00001489326,0.0001235355,0.00002530291,0.000222681],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000001906269,0.000012268,0.9853344,0.00007762972,0.0001027956,3.249939e-7,0.0000245438,0.00001559505,0.00009070847,0.005107352,0.0004381172,0.008794362],"study_design_scores_gemma":[0.0001540267,0.000003502281,0.9903578,0.00002930317,0.0001968803,2.87131e-8,0.00002970375,0.0005986647,0.0000771264,0.008015176,0.0004325474,0.0001052532],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9863224,0.001720447,0.005534005,0.0008717637,0.00003692564,0.0001508137,0.00003883932,0.0002555588,0.005069225],"genre_scores_gemma":[0.999211,0.00003963442,0.0005680618,0.00007058174,0.00001928883,0.00003692921,0.00001172151,0.000004940306,0.00003781247],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01288861,"threshold_uncertainty_score":0.3578073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01051231476501507,"score_gpt":0.266159541260386,"score_spread":0.255647226495371,"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."}}