{"id":"W2054490650","doi":"10.1109/ultsym.2007.566","title":"P5C-4 Image Guidance Using Camera and Ultrasound Images","year":2007,"lang":"en","type":"article","venue":"Proceedings/Proceedings - IEEE Ultrasonics Symposium","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer vision; Artificial intelligence; Orientation (vector space); Computer science; Ultrasound; Volume (thermodynamics); Position (finance); Tracking (education); Trajectory; 3D ultrasound; Mathematics; Medicine; 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":[0.000762283,0.0005885855,0.0004871937,0.001374269,0.0003472867,0.00169638,0.001122767,0.001395428,0.006914075],"category_scores_gemma":[0.003854338,0.0004512715,0.0003712929,0.001018428,0.0004318122,0.001072,0.000753191,0.0005352278,0.001946332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008418878,"about_ca_system_score_gemma":0.001018382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008731795,"about_ca_topic_score_gemma":0.0086559,"domain_scores_codex":[0.9985884,0.0001743285,0.0000580434,0.0002731789,0.0008251492,0.00008084346],"domain_scores_gemma":[0.9985731,0.000293905,0.000115111,0.0002347252,0.0007297551,0.00005350453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006556988,0.0001086932,0.003471074,0.0003949841,0.0001184076,0.0004711808,0.0002404851,0.03934391,0.2433708,0.004264295,0.005662693,0.7018978],"study_design_scores_gemma":[0.00007321396,0.000571374,0.01556944,0.00009482238,0.00008985593,0.001842726,0.0001286927,0.6482861,0.3002323,0.001321131,0.03165277,0.0001376653],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03668968,0.0003605404,0.9521908,0.00009309816,0.00006999193,0.0002071221,0.0001764865,0.002797523,0.007414614],"genre_scores_gemma":[0.3790093,0.000366607,0.6086402,0.0001734062,0.00003387747,0.0001579658,0.0005700344,0.0004013827,0.01064719],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008731795,"threshold_uncertainty_score":0.02312988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008908398713248052,"score_gpt":0.2340134084457892,"score_spread":0.2251050097325412,"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."}}