{"id":"W4411907405","doi":"10.1002/adhm.202403423","title":"Kidney Stone Dissolution By Tetherless, Enzyme‐Loaded, Soft Magnetic Miniature Robots","year":2025,"lang":"en","type":"article","venue":"Advanced Healthcare Materials","topic":"Micro and Nano Robotics","field":"Physics and Astronomy","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research Institute for Aging; St. Michael's Hospital; National Institute for Nanotechnology; University of Toronto; University of Waterloo","funders":"Agencia Estatal de Investigación; Generalitat de Catalunya; Natural Sciences and Engineering Research Council of Canada; Centres de Recerca de Catalunya; “la Caixa” Foundation","keywords":"Urinary system; Medicine; Kidney stones; Kidney; Kidney disease; Population; Targeted drug delivery; Uric acid; Urease; Urology; Surgery; Drug; Internal medicine; Pharmacology; Urea; Chemistry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000147191,0.0002952418,0.0004586808,0.0000681025,0.0002399425,0.00006763172,0.0002224583,0.0001478497,0.0006480642],"category_scores_gemma":[0.00002043035,0.0002851862,0.00007036199,0.000219193,0.00005860434,0.0001332137,0.00006513973,0.0001769764,0.00007482887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007854446,"about_ca_system_score_gemma":0.0002148369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000427279,"about_ca_topic_score_gemma":0.00001095577,"domain_scores_codex":[0.9982687,0.0001463496,0.0004455349,0.0004404359,0.0001412869,0.000557646],"domain_scores_gemma":[0.9990448,0.00005325197,0.0001860059,0.0004109474,0.0001058019,0.0001992186],"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":[0.0001383499,0.0001388917,0.0008348557,0.0003460448,0.00004087814,0.000001878899,0.0001791584,0.000102243,0.9271765,0.009149634,0.03846681,0.02342471],"study_design_scores_gemma":[0.002218914,0.000195005,0.001423679,0.0006331927,0.00008220129,0.000001719707,0.0004372241,0.00001849369,0.8750958,0.007433014,0.1117494,0.0007112627],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8411541,0.02345624,0.05922636,0.04402732,0.01300251,0.004982037,0.00848829,0.0007958442,0.004867275],"genre_scores_gemma":[0.9890783,0.00007852832,0.002480905,0.001454769,0.0003035419,0.00009319109,0.0008586054,0.00004222398,0.005609885],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1479242,"threshold_uncertainty_score":0.99996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006116004540701847,"score_gpt":0.2719935768503113,"score_spread":0.2658775723096095,"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."}}