{"id":"W2995773737","doi":"10.3390/jcm8122181","title":"Retinal Microperimetry: A Useful Tool for Detecting Insulin Resistance-Related Cognitive Impairment in Morbid Obesity","year":2019,"lang":"en","type":"article","venue":"Journal of Clinical Medicine","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fondazione Internazionale Menarini","keywords":"Microperimetry; Medicine; Retinal; Insulin resistance; Montreal Cognitive Assessment; Neurocognitive; Internal medicine; Cognition; Diabetes mellitus; Cognitive decline; Dementia; Repeatable Battery for the Assessment of Neuropsychological Status; Ophthalmology; Cognitive impairment; Audiology; Obesity; Endocrinology; Psychiatry; 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006339901,0.0002024644,0.001582453,0.0003590897,0.00004186833,0.00001152268,0.0001477652,0.0001701668,0.0002313011],"category_scores_gemma":[0.01083947,0.0001340121,0.0005056741,0.0005474632,0.0001978966,0.00009560045,0.00003380953,0.00113403,0.00002321151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009813023,"about_ca_system_score_gemma":0.0002348962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002466903,"about_ca_topic_score_gemma":0.000006705469,"domain_scores_codex":[0.9958536,0.0002839626,0.002679224,0.0003108404,0.0005576572,0.0003147324],"domain_scores_gemma":[0.9954236,0.002055675,0.001280588,0.000217268,0.0007610951,0.0002617878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01497411,0.0008631757,0.9611819,0.000367223,0.0005367527,0.0004574897,0.0003896781,0.000004885112,0.004285909,0.00001113675,0.001335888,0.01559179],"study_design_scores_gemma":[0.03244846,0.010988,0.9361756,0.01059952,0.001431684,0.0004358522,0.001742223,0.0006729177,0.001981962,0.0003292452,0.002914081,0.0002804683],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905127,0.001380402,0.0004228675,0.005455173,0.0005218611,0.0004764416,0.000003166635,0.00001349135,0.001213933],"genre_scores_gemma":[0.9940315,0.0003652396,0.002659793,0.0009155421,0.0008193175,0.000003377831,0.000005217607,0.00002561491,0.001174415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02500637,"threshold_uncertainty_score":0.9974927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04008246298256223,"score_gpt":0.397986075863849,"score_spread":0.3579036128812868,"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."}}