{"id":"W2034615828","doi":"10.1117/12.770449","title":"Registration of a needle-positioning robot to high-resolution 3D ultrasound and computed tomography for image-guided interventions in small animals","year":2008,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"","keywords":"Fiducial marker; Imaging phantom; Computer vision; Robot; Artificial intelligence; Iterative closest point; Computer science; Image registration; Ultrasound; Nuclear medicine; Image (mathematics); Medicine; Radiology; Point cloud","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":[0.00111528,0.0003509349,0.0003186949,0.0003508208,0.0002543234,0.0005695274,0.0008671329,0.0006974061,0.002115341],"category_scores_gemma":[0.003120998,0.0004425067,0.0004510418,0.0002813632,0.000587857,0.0006366649,0.0006409489,0.0007189329,0.0007804073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006340765,"about_ca_system_score_gemma":0.00121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001511321,"about_ca_topic_score_gemma":0.002510029,"domain_scores_codex":[0.9993021,0.0001617839,0.00004339501,0.00009472053,0.0003567413,0.00004118294],"domain_scores_gemma":[0.998985,0.000399725,0.0002439037,0.0002176015,0.0001151178,0.00003862357],"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":[0.0004293636,0.0002277577,0.00283424,0.0002811874,0.00006247921,0.0004502817,0.0003444333,0.1178016,0.8000311,0.005739074,0.001025523,0.07077294],"study_design_scores_gemma":[0.0001030525,0.001922827,0.01013565,0.00004931572,0.00009307461,0.001226494,0.0001035996,0.3701612,0.5936417,0.002580595,0.01984734,0.000135206],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08147582,0.0001785113,0.9147305,0.0001363378,0.00005921531,0.0002669684,0.0000751457,0.001258721,0.001818753],"genre_scores_gemma":[0.4084147,0.0002755869,0.5876405,0.00008920832,0.00001563112,0.0004253484,0.0001861933,0.000200271,0.002752571],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002115341,"threshold_uncertainty_score":0.007076502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02214873834456328,"score_gpt":0.2421888600895064,"score_spread":0.2200401217449431,"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."}}