{"id":"W4287755426","doi":"10.3791/60946-v","title":"Using a Chemical Biopsy for Graft Quality Assessment","year":2020,"lang":"en","type":"article","venue":"Journal of Visualized Experiments","topic":"Renal Transplantation Outcomes and Treatments","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; University Health Network","funders":"University of Waterloo; Merck KGaA","keywords":"Transplantation; Biopsy; Kidney transplantation; Medicine; Sampling (signal processing); Computer science; Pathology; Surgery","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000161558,0.0001372249,0.0004953415,0.00005562314,0.00003941196,0.00002174804,0.00006945345,0.00005589998,0.00008382302],"category_scores_gemma":[0.00004626831,0.0001007548,0.0003285447,0.0000999185,0.00002324532,0.00009833718,0.00001162184,0.0001016164,0.000002738626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001107657,"about_ca_system_score_gemma":0.0001219751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006161242,"about_ca_topic_score_gemma":1.865169e-8,"domain_scores_codex":[0.9986123,0.00004680492,0.0006481878,0.0001314119,0.0004036107,0.0001576776],"domain_scores_gemma":[0.9990531,0.00005890768,0.0003645153,0.00007595118,0.0001623366,0.0002852244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002518868,0.0006691923,0.0150764,0.0002203671,0.000720636,0.000115802,0.0007734856,0.000004880569,0.9791982,0.0003364561,0.00007791165,0.0002877698],"study_design_scores_gemma":[0.0399001,0.001822685,0.009830908,0.0006145764,0.0007960247,0.0006172745,0.0008175795,0.001480329,0.94231,0.0001549583,0.001342686,0.0003128303],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9524003,0.0002576633,0.04584243,0.0006918614,0.0001909345,0.0003639405,0.00001832036,0.00001543183,0.0002190642],"genre_scores_gemma":[0.8924828,0.0000248121,0.1064396,0.0008014499,0.0001858204,0.000006487006,0.00001519782,0.00001942789,0.000024439],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06059714,"threshold_uncertainty_score":0.4108662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2168030986002836,"score_gpt":0.5648272314742799,"score_spread":0.3480241328739963,"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."}}