{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001766193,0.0002912781,0.0002916552,0.001074744,0.0003179717,0.000729014,0.0003586923,0.000534675,0.001419377],"category_scores_gemma":[0.01001975,0.0002310004,0.0005277472,0.0009729906,0.0002800213,0.0005769237,0.0004990006,0.0005554442,0.0001132135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001929845,"about_ca_system_score_gemma":0.0002219613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003333035,"about_ca_topic_score_gemma":0.003980933,"domain_scores_codex":[0.998904,0.000299991,0.0002616837,0.0001912251,0.0002461111,0.00009687396],"domain_scores_gemma":[0.99091,0.002388363,0.00481345,0.0005141775,0.0009301668,0.0004438786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007238954,0.00001163982,0.9986787,0.00001197754,0.00007812097,0.00005747675,0.00003566172,0.00001816687,0.0001429147,0.000005841833,0.00002020169,0.0008666725],"study_design_scores_gemma":[0.000001936173,0.00004243181,0.999334,0.000005515344,0.0000339072,0.000339936,0.000044206,0.0001010002,0.00003898328,0.00001470541,0.00004120625,0.000002143673],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981486,0.0009225806,0.000281857,0.00005591901,0.000007470066,0.0000110625,0.00020308,0.000005904802,0.0003636733],"genre_scores_gemma":[0.9993974,0.0001489156,0.0002096766,0.00001912165,0.00001085818,0.000004675398,0.000127961,0.000001432526,0.00007996679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003333035,"threshold_uncertainty_score":0.009340644,"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."}}