{"id":"W2730741013","doi":"","title":"Correlation between leptin receptor gene polymorphism and type 2 diabetes in Chinese population: a meta-analysis","year":2015,"lang":"en","type":"article","venue":"Jiefangjun yixue zazhi","topic":"Regulation of Appetite and Obesity","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Meta-analysis; Allele; Leptin receptor; Genetic model; Polymorphism (computer science); Type 2 diabetes; Genetics; Population; Correlation; Internal medicine; Leptin; Genotype; Biology; Medicine; Gene; Diabetes mellitus; Endocrinology; Obesity","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":[0.0004847937,0.0002079954,0.0006232679,0.0004291465,0.00009979274,0.00008349665,0.0001401159,0.0001294116,0.0002739802],"category_scores_gemma":[0.0004746822,0.000170789,0.0002246624,0.001785337,0.00006332785,0.0004009302,0.00008488091,0.0001498827,0.0001388806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005430441,"about_ca_system_score_gemma":0.00002470843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002469782,"about_ca_topic_score_gemma":0.0001195312,"domain_scores_codex":[0.9982165,0.0002462578,0.0003986539,0.0004865789,0.0004036782,0.0002483991],"domain_scores_gemma":[0.9989893,0.0002205661,0.0001973535,0.0003513579,0.00006692469,0.0001745205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002364059,0.00004592658,0.9917001,0.000005838944,0.0007608026,0.000004463209,0.0002447048,0.001356782,0.004927147,0.0002678436,0.0003884177,0.000274316],"study_design_scores_gemma":[0.0005126404,0.00008128944,0.9814826,0.000002641484,0.004523944,0.000002066014,0.00001434957,0.005081327,0.00550105,0.001015862,0.001472972,0.0003092181],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973632,0.0004195078,0.000113897,0.001048091,0.0001630279,0.0002097026,0.00002858038,0.00006809003,0.0005859306],"genre_scores_gemma":[0.9972764,0.00001540897,0.000582688,0.0002843536,0.0001664957,0.0000111885,0.0001026067,0.00001819344,0.00154263],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01021748,"threshold_uncertainty_score":0.6964573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07195953219793141,"score_gpt":0.29373540864061,"score_spread":0.2217758764426786,"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."}}