{"id":"W2538075778","doi":"10.1109/iembs.2004.1403551","title":"A haptic-based system for medical image examination","year":2005,"lang":"en","type":"article","venue":"","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Queen's University","funders":"Canadian Space Agency","keywords":"Haptic technology; Computer science; Interface (matter); Medical simulation; Computer vision; Medical physics; Position (finance); Artificial intelligence; Virtual reality; Medical imaging; Simulation; Virtual image; Operator (biology); Virtual patient; Human–computer interaction; Computer graphics (images); Medicine","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":[0.0002607662,0.00006476149,0.00008758327,0.00004627949,0.00002792449,0.00003465637,0.00005949603,0.00006272858,0.000334611],"category_scores_gemma":[0.00003759145,0.00005634054,0.00003066812,0.00004064554,0.000008059306,0.00007171755,0.000002527977,0.00003128609,0.0001972612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007241521,"about_ca_system_score_gemma":0.00001724515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003748774,"about_ca_topic_score_gemma":0.00004372995,"domain_scores_codex":[0.9994654,0.00001152188,0.0001793131,0.00007383047,0.0001629514,0.0001069635],"domain_scores_gemma":[0.9997298,0.00005853248,0.000008854799,0.0000902554,0.00004101761,0.00007152522],"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":[0.00003987032,0.0002832688,0.0002054115,0.004045228,0.0002404901,0.00002861266,0.002169379,0.03592812,0.1415786,0.2778739,0.09860716,0.439],"study_design_scores_gemma":[0.0005318433,0.00001184689,0.0001770797,0.00002930942,0.000004431004,0.000006115551,0.0001154994,0.9731646,0.004370459,9.5985e-7,0.02150953,0.00007838525],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0222459,0.00003820872,0.9282565,0.0003712402,0.000343318,0.0002995105,0.000004050052,0.0009093194,0.04753198],"genre_scores_gemma":[0.9903268,6.030187e-7,0.008630627,0.00008537916,0.0002871422,0.00007729203,0.000009076508,0.0000163171,0.0005667939],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9680809,"threshold_uncertainty_score":0.3663756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00854219728858731,"score_gpt":0.2211696809576845,"score_spread":0.2126274836690972,"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."}}