{"id":"W2161746608","doi":"10.1109/ultsym.2015.0170","title":"Ultrasonic characterization of extra-cellular matrix in decellularized murine kidney and liver","year":2015,"lang":"en","type":"article","venue":"","topic":"Tissue Engineering and Regenerative Medicine","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Decellularization; Kidney; Extracellular matrix; Matrix (chemical analysis); Cell biology; Characterization (materials science); Biomedical engineering; Computer science; Materials science; Biology; Nanotechnology; Medicine; Internal medicine; Composite material","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":[0.0002074976,0.0001037776,0.0002734975,0.0001368187,0.000007741574,0.00000323342,0.00002661789,0.00006441887,0.0001117388],"category_scores_gemma":[0.0001510296,0.00007684399,0.00002073215,0.0001658867,0.00004910528,0.00003933507,0.00001146029,0.00009978902,0.000007472284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002564155,"about_ca_system_score_gemma":0.00006368267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005286295,"about_ca_topic_score_gemma":0.000001595533,"domain_scores_codex":[0.9993455,0.00002545785,0.0002158331,0.0001403501,0.0001501939,0.0001226504],"domain_scores_gemma":[0.9995283,0.00001570295,0.00003869315,0.0001256222,0.00006133044,0.0002302801],"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":[0.00006173171,0.00008375528,0.00758168,0.0001297923,0.00001751665,0.00005806384,0.0004350671,0.000007197221,0.9900718,0.0006580952,0.0001016036,0.0007936787],"study_design_scores_gemma":[0.01298777,0.0008957334,0.0399113,0.0006227061,0.0001451705,0.0001753347,0.0002346129,0.01791137,0.89947,0.0000224521,0.02729522,0.0003283001],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9815138,0.002281331,0.0149317,0.0005604681,0.0001416421,0.0002283264,0.000002937922,0.00003857381,0.0003012503],"genre_scores_gemma":[0.9834955,0.0001990065,0.00211056,0.00003409272,0.000115567,0.00000527621,0.0000864288,0.00001525834,0.01393828],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09060178,"threshold_uncertainty_score":0.3133607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01812607247655499,"score_gpt":0.2493245372232687,"score_spread":0.2311984647467137,"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."}}