{"id":"W94365490","doi":"10.1007/978-3-642-33415-3_6","title":"Remote Ultrasound Palpation for Robotic Interventions Using Absolute Elastography","year":2012,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Imaging phantom; Elastography; Computer science; Transducer; Palpation; Ultrasound; Biomedical engineering; Haptic technology; Computer vision; Robotics; Acoustics; Stiffness; Artificial intelligence; Robot; Medicine; Surgery; Radiology; Materials science; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006296079,0.0001562796,0.0002089333,0.0006337238,0.000258467,0.00008505317,0.0001782931,0.00005938911,0.000008108606],"category_scores_gemma":[0.000261978,0.0001378165,0.0002272684,0.00159515,0.0003347066,0.0003606455,0.0000551846,0.0001983801,0.000003845396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008276806,"about_ca_system_score_gemma":0.00006362881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004366873,"about_ca_topic_score_gemma":0.00001839285,"domain_scores_codex":[0.9985331,0.00002803341,0.0002669637,0.0003384434,0.0002649303,0.0005684838],"domain_scores_gemma":[0.9989607,0.0003469603,0.00008817833,0.0003092967,0.0001343923,0.0001604246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001151959,0.0008216191,0.3344513,0.0005486449,0.0001092048,0.00000239029,0.004782741,0.1397417,0.1303483,0.0001098834,0.00005067157,0.3889183],"study_design_scores_gemma":[0.002113506,0.0007704096,0.3289141,0.001712206,0.0002777658,0.0007526542,0.00001581686,0.6485207,0.008016622,0.007683334,0.0004255713,0.0007973209],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2404469,0.0003471671,0.7577247,0.0001822455,0.0009833057,0.000253386,9.890213e-7,0.00005202181,0.000009328088],"genre_scores_gemma":[0.5942569,0.000004119265,0.4051961,0.0002783551,0.0002473137,0.000002698318,0.000004823684,0.000009053987,6.377946e-7],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5087789,"threshold_uncertainty_score":0.5619996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03262503335892836,"score_gpt":0.318175687542007,"score_spread":0.2855506541830786,"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."}}