{"id":"W3017326594","doi":"10.1172/jci.insight.136995","title":"Photoacoustic imaging of kidney fibrosis for assessing pretransplant organ quality","year":2020,"lang":"en","type":"article","venue":"JCI Insight","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Toronto Metropolitan University; St. Michael's Hospital","funders":"Banting and Best Diabetes Centre, University of Toronto; Canadian Institutes of Health Research; St. Michael's Hospital Foundation; Natural Sciences and Engineering Research Council of Canada; Canadian Society of Transplantation; St. Michael’s Hospital Foundation","keywords":"Medicine; Kidney disease; Fibrosis; Kidney; Kidney transplantation; Transplantation; Nephrogenic systemic fibrosis; Pathology; Nephrology; Renal function; Population; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001031392,0.0003978463,0.000214824,0.000783478,0.0001922583,0.0005187176,0.0002916221,0.0008020591,0.00154581],"category_scores_gemma":[0.0009196277,0.0002465585,0.0002446271,0.0003483196,0.0003943698,0.0007980373,0.0004125253,0.0009004922,0.0003530882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002404536,"about_ca_system_score_gemma":0.0004103718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004237122,"about_ca_topic_score_gemma":0.001155652,"domain_scores_codex":[0.9997118,0.00009424915,0.00001229417,0.00005007831,0.0001006423,0.00003101322],"domain_scores_gemma":[0.9995003,0.0002404011,0.00009565552,0.00003553076,0.00008052836,0.00004755571],"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":[0.00008309531,0.00004738775,0.003062935,0.0001928504,0.00001710131,0.0001008455,0.00004998151,0.000512716,0.9599469,0.0006619294,0.0004823802,0.03484197],"study_design_scores_gemma":[0.00003245545,0.0006814617,0.0298033,0.0001383974,0.0001149921,0.002494212,0.0001966469,0.03834427,0.9147078,0.001832329,0.01157282,0.00008122345],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2740018,0.02413069,0.6891236,0.001644587,0.0004287265,0.0002965818,0.000290653,0.000845261,0.009238128],"genre_scores_gemma":[0.6637663,0.01319622,0.3191449,0.0007345032,0.0001913316,0.0002240518,0.0001261054,0.00007568795,0.002540932],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00154581,"threshold_uncertainty_score":0.0054546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02054325183979093,"score_gpt":0.252921944402109,"score_spread":0.2323786925623181,"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."}}