{"id":"W2058403906","doi":"10.1007/s10765-012-1286-x","title":"Study of Tissue Phantoms, Tissues, and Contrast Agent with the Biophotoacoustic Radar and Comparison to Ultrasound Imaging for Deep Subsurface Imaging","year":2012,"lang":"en","type":"article","venue":"International Journal of Thermophysics","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; University of Toronto","funders":"","keywords":"Imaging phantom; Materials science; Biomedical engineering; Ultrasound; Molecular imaging; Photoacoustic imaging in biomedicine; Medical imaging; Contrast (vision); Microbubbles; Optics; Medicine; Nuclear medicine; In vivo; Radiology; Physics","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":[0.0007451522,0.0004941506,0.0003364763,0.0003922305,0.0002045892,0.0002325404,0.0002439826,0.0003980757,0.0009205061],"category_scores_gemma":[0.001339442,0.0002948424,0.0001639835,0.0003592626,0.000385028,0.0004442281,0.0002529332,0.0002639556,0.000139161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001085266,"about_ca_system_score_gemma":0.0002195417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005091145,"about_ca_topic_score_gemma":0.0006176523,"domain_scores_codex":[0.9997748,0.00009611446,0.00001140284,0.00002853063,0.0000650583,0.00002410234],"domain_scores_gemma":[0.9984309,0.001126286,0.000125947,0.0001326895,0.0001298579,0.00005427897],"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":[0.0001805308,0.00005399827,0.0001635369,0.00007327289,0.000007689247,0.0000708817,0.00005152526,0.0005921473,0.996614,0.00021566,0.00004250191,0.001934128],"study_design_scores_gemma":[0.00002949541,0.001513707,0.002656904,0.0000204319,0.00006356181,0.001214278,0.00008524708,0.006308044,0.9852106,0.0001793239,0.002701433,0.00001695847],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8823493,0.005190114,0.1084387,0.0002140624,0.00006088003,0.0001807749,0.0001965906,0.0002614331,0.003108216],"genre_scores_gemma":[0.9484431,0.002260454,0.04507384,0.0001225377,0.00002182199,0.0001137657,0.0002522503,0.0001133226,0.003598898],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009205061,"threshold_uncertainty_score":0.003940761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009462621345212535,"score_gpt":0.2650052198856246,"score_spread":0.2555425985404121,"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."}}