{"id":"W4401388414","doi":"10.1016/j.matt.2024.04.021","title":"Seeing through deep tissue mechanics with wearable ultrasound","year":2024,"lang":"en","type":"article","venue":"Matter","topic":"Cellular Mechanics and Interactions","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Bioadhesive; Elastography; Ultrasound elastography; Ultrasound; Medicine; Biomedical engineering; Wearable computer; Disease monitoring; Mechanobiology; Stiffness; Disease; In vivo; Radiology; Computer science; Pathology; Nanotechnology; Materials science; Drug delivery; Anatomy; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003757718,0.0005736686,0.0003774193,0.0002986618,0.0002800718,0.001088246,0.0004802693,0.0008988235,0.004786564],"category_scores_gemma":[0.001380574,0.0004553402,0.0002737749,0.0003874824,0.001120191,0.002109124,0.002021341,0.000843123,0.0008812521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001961997,"about_ca_system_score_gemma":0.0001747567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002139114,"about_ca_topic_score_gemma":0.0004326977,"domain_scores_codex":[0.999693,0.00005621369,0.00001246998,0.00006089463,0.0001417982,0.00003553795],"domain_scores_gemma":[0.999239,0.0004099255,0.0001043146,0.0001079209,0.00006415445,0.0000746055],"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":[0.0001346363,0.00006243822,0.001617682,0.0003184932,0.00003501785,0.0003267145,0.0007311496,0.002985559,0.9279052,0.006419885,0.001497625,0.05796561],"study_design_scores_gemma":[0.0001309412,0.002414057,0.03174765,0.0004313618,0.000261173,0.005144138,0.002836595,0.1420298,0.6916085,0.06960851,0.05336699,0.0004202539],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4837873,0.008263208,0.4755106,0.00219139,0.0007873953,0.0001337412,0.0003939497,0.001766237,0.02716615],"genre_scores_gemma":[0.9158919,0.003337641,0.06814932,0.001052421,0.0003694298,0.00007801873,0.0001145909,0.0002014206,0.01080514],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004786564,"threshold_uncertainty_score":0.01601261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005502171969224446,"score_gpt":0.2344177810478023,"score_spread":0.2289156090785779,"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."}}