{"id":"W1970587623","doi":"10.5301/jn.5000205","title":"Microarray applications in nephrology with special focus on transplantation","year":2012,"lang":"en","type":"review","venue":"Journal of Nephrology","topic":"Renal Transplantation Outcomes and Treatments","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Medicine; Transcriptome; Nephrology; Kidney transplantation; Disease; Transplantation; Gene expression profiling; Bioinformatics; Kidney disease; Computational biology; Microarray; End stage renal disease; Internal medicine; Gene; Gene expression; Biology; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001476329,0.0003435889,0.001788659,0.0007114683,0.00003618334,0.000007785397,0.0001342682,0.0003945673,0.0001651789],"category_scores_gemma":[0.000002981604,0.0002052633,0.0003907463,0.0002843389,0.00008285288,0.0000741179,0.000004049429,0.0007059147,0.00006433808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001496312,"about_ca_system_score_gemma":0.0002781991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008935913,"about_ca_topic_score_gemma":0.00006176503,"domain_scores_codex":[0.9981636,0.0001777331,0.0009255092,0.0002055801,0.0002186642,0.0003089326],"domain_scores_gemma":[0.9985064,0.0003016978,0.0007646613,0.0001876702,0.00008142488,0.0001581986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004439605,0.001832393,0.00226971,0.01217021,0.002699815,0.003233469,0.0006217904,0.00001094358,0.00004068332,0.001714234,0.0002876637,0.9706795],"study_design_scores_gemma":[0.003299231,0.001665119,0.003740045,0.002832724,0.004901032,0.01145413,0.00001068687,1.245649e-7,0.000005886802,0.00008434652,0.9718401,0.0001666078],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0007522914,0.9947401,0.0006582689,0.0004344182,0.0002498205,0.001183696,0.00005218345,0.00001032242,0.001918894],"genre_scores_gemma":[0.0005218567,0.9959816,0.00100797,0.0004792136,0.001688802,0.00005194403,0.0001299968,0.00004286027,0.00009574642],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9715524,"threshold_uncertainty_score":0.8370395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0393264967248477,"score_gpt":0.3335272788250055,"score_spread":0.2942007821001579,"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."}}