{"id":"W2148558227","doi":"10.1109/titb.2008.926496","title":"A Framework for the Design of a Novel Haptic-Based Medical Training Simulator","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Information Technology in Biomedicine","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Haptic technology; Kinesthetic learning; Computer science; Modular design; Medical simulation; Imaging phantom; Simulation; Software; Computer architecture simulator; Ultrasound; Medical physics; Radiology; Medicine","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":[0.001347688,0.0009138537,0.0006546732,0.000718876,0.0005917964,0.001651182,0.003414072,0.001699208,0.006912337],"category_scores_gemma":[0.001845739,0.0006145249,0.001004863,0.0002374143,0.001076002,0.001009268,0.001697512,0.001291079,0.002153967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006494342,"about_ca_system_score_gemma":0.001841444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001908262,"about_ca_topic_score_gemma":0.001229199,"domain_scores_codex":[0.9990262,0.0002144647,0.00008399463,0.00013086,0.0004682834,0.00007622888],"domain_scores_gemma":[0.9994515,0.0001565142,0.00005583954,0.00007331847,0.0001808341,0.00008191694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002716123,0.0003149987,0.001067551,0.001429564,0.0001348732,0.001003297,0.001466067,0.379798,0.110294,0.3057362,0.0068644,0.1916194],"study_design_scores_gemma":[0.0001652988,0.0004953542,0.0004666274,0.0003120088,0.00008312739,0.0007804901,0.0001438193,0.8098453,0.02031843,0.02422952,0.1430455,0.0001146134],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001072958,0.00006478956,0.9958928,0.00006977079,0.00002874833,0.0002046345,0.00003245111,0.000800437,0.001833533],"genre_scores_gemma":[0.05108489,0.0002306972,0.9429768,0.00008053777,0.00003069916,0.0008889788,0.0001531107,0.0001808871,0.004373398],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006912337,"threshold_uncertainty_score":0.0231241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0743624826659165,"score_gpt":0.3270926994348333,"score_spread":0.2527302167689168,"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."}}