{"id":"W4386084393","doi":"10.1111/dom.15243","title":"Impact of sarcosine on diabetic retinopathy: Findings based on weighted gene co‐expression network analysis and machine learning techniques","year":2023,"lang":"en","type":"article","venue":"Diabetes Obesity and Metabolism","topic":"Retinal Diseases and Treatments","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"Zhejiang University; Anhui Medical University; Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China; Wenzhou Medical University","keywords":"Sarcosine; Odds ratio; Internal medicine; Medicine; Diabetic retinopathy; Logistic regression; Confidence interval; Interquartile range; Body mass index; Diabetes mellitus; Endocrinology; Bioinformatics; Oncology; Genetics; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001040445,0.0003677639,0.0003540738,0.001487597,0.0001883618,0.0004596373,0.0002531609,0.0002289138,0.000598054],"category_scores_gemma":[0.002608838,0.0001043515,0.00061043,0.001624684,0.0002626464,0.0003985777,0.0003434989,0.0002901924,0.0000873302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002741385,"about_ca_system_score_gemma":0.0002528659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003266193,"about_ca_topic_score_gemma":0.003450451,"domain_scores_codex":[0.9994792,0.0002465491,0.00002256834,0.0001422615,0.00007268224,0.00003676724],"domain_scores_gemma":[0.9986376,0.0007173146,0.0003884534,0.0001036027,0.00009749571,0.00005549361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001398906,0.0001278979,0.8255191,0.0003912274,0.0021764,0.0003516474,0.000238129,0.03542342,0.0310608,0.001460368,0.0007063297,0.1011458],"study_design_scores_gemma":[0.00002609295,0.0002435255,0.7519965,0.00005404116,0.0007525154,0.0006383665,0.0001889477,0.2359811,0.004256524,0.004374413,0.00145352,0.00003449759],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9569167,0.002865226,0.03845186,0.0002635158,0.00001715912,0.00002219253,0.0006731468,0.00007991731,0.0007103828],"genre_scores_gemma":[0.9914311,0.0005968801,0.007348879,0.00003104397,0.00001482256,0.00001788352,0.0003946514,0.000007987957,0.0001568744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003266193,"threshold_uncertainty_score":0.006494343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009477936432036555,"score_gpt":0.2664616575259388,"score_spread":0.2569837210939023,"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."}}