{"id":"W2140501115","doi":"10.1109/iembs.2007.4353046","title":"One-step Needle Pose Estimation for Ultrasound Guided Biopsies","year":2007,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Artificial intelligence; Computer vision; Computer science; Orientation (vector space); Position (finance); Pose; USB; Parametric statistics; Line (geometry); Tracking (education); Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002036755,0.0001368973,0.0001423868,0.0001148954,0.00008175631,0.000138755,0.0001102906,0.0001056379,0.00002595805],"category_scores_gemma":[0.0001914563,0.0001535141,0.00003684128,0.0001825613,0.00003510691,0.0002228139,0.000008812313,0.00007178392,0.00001793659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005623784,"about_ca_system_score_gemma":0.00001693417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008458788,"about_ca_topic_score_gemma":0.000004244349,"domain_scores_codex":[0.9991708,9.850137e-7,0.000259414,0.0001583794,0.0001341727,0.0002762037],"domain_scores_gemma":[0.9994121,0.00005899285,0.00004575767,0.00006569508,0.0003366002,0.00008089581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001102767,0.0001649865,0.00591186,0.00178198,0.0001560962,0.000002185924,0.0068145,0.06929713,0.6550345,0.1816803,0.02382515,0.05522104],"study_design_scores_gemma":[0.0004566375,0.0000686097,0.002011642,0.00009513952,0.00003382208,0.000008644984,0.0005638553,0.9067943,0.08474594,0.003408516,0.001483879,0.0003290253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.25289,0.0000386316,0.7397408,0.00008336073,0.0002315586,0.000320418,0.000005773285,0.0003288792,0.006360583],"genre_scores_gemma":[0.9668646,0.00002360973,0.03272168,0.00005584387,0.0001123942,0.00001656935,0.00003772652,0.00003056235,0.0001370179],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8374972,"threshold_uncertainty_score":0.6260124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03329259900080395,"score_gpt":0.2561563479256844,"score_spread":0.2228637489248804,"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."}}