{"id":"W4220788699","doi":"10.36227/techrxiv.19295948.v1","title":"photoacoustic imaging with photoacoustic markers: an ex vivo demonstration","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Johns Hopkins University; National Institutes of Health; Intuitive Surgical; National Science Foundation","keywords":"Photoacoustic imaging in biomedicine; Ultrasound; Medicine; Transducer; Ex vivo; Surgical robot; Medical imaging; Nuclear medicine; Biomedical engineering; Radiology; In vivo; Computer science; Artificial intelligence; Robot; Physics; Acoustics; Optics","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":[0.0006282452,0.0004738403,0.0002430393,0.0002408765,0.0001423698,0.0003931363,0.0004455508,0.0007678564,0.001048515],"category_scores_gemma":[0.0007499272,0.0003405535,0.0002244741,0.0001831195,0.0004021598,0.0007153129,0.0004825852,0.0005956066,0.0005020993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001160883,"about_ca_system_score_gemma":0.0002081108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002645817,"about_ca_topic_score_gemma":0.000268371,"domain_scores_codex":[0.9997435,0.00006649774,0.00001372044,0.00006643132,0.00008174872,0.00002810675],"domain_scores_gemma":[0.9995686,0.0001782661,0.00008710263,0.00007710671,0.0000521657,0.00003663611],"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":[0.0001023404,0.00006533197,0.0002752523,0.00007880623,0.00000634394,0.0002216041,0.0001036014,0.0005173414,0.9882284,0.0001962944,0.0001151453,0.01008951],"study_design_scores_gemma":[0.00003222962,0.001496653,0.003875955,0.00002885845,0.00003910481,0.00283132,0.0001020212,0.01448685,0.9709654,0.0002409562,0.005864488,0.00003611816],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6390639,0.002868593,0.3535862,0.0003110493,0.0001563666,0.000148558,0.0001244699,0.0008323695,0.002908476],"genre_scores_gemma":[0.8643736,0.001877923,0.1297159,0.0001136259,0.00007144051,0.0001620932,0.0001262602,0.0001261402,0.003433101],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001048515,"threshold_uncertainty_score":0.003507614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008001471464962509,"score_gpt":0.2157076732563209,"score_spread":0.2077062017913584,"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."}}