{"id":"W2889390764","doi":"10.1109/vr.2018.8446310","title":"User Performance of VR-Based Tissue Dissection Under the Effects of Force Models and Tracing Speeds","year":2018,"lang":"en","type":"article","venue":"","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Workload; Virtual reality; Computer science; Simulation; Surgical simulation; Tracing; Haptic technology; Work (physics); Dissection (medical); Human–computer interaction; Surgery; Medicine; Engineering","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":[0.0007495672,0.0004541746,0.0002893261,0.0002927305,0.0001271308,0.0005279661,0.0002507243,0.0003882567,0.001998755],"category_scores_gemma":[0.007055409,0.0001816746,0.0002967867,0.0001193961,0.0002449153,0.0003533197,0.0004801885,0.0001576559,0.0003270862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009598747,"about_ca_system_score_gemma":0.0001332604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001040404,"about_ca_topic_score_gemma":0.0008189931,"domain_scores_codex":[0.9995329,0.0001847687,0.00004656209,0.00009338517,0.00009075212,0.00005148982],"domain_scores_gemma":[0.9960135,0.002922153,0.0003344768,0.0002479161,0.0002961829,0.0001856777],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.01531355,0.002265132,0.1454033,0.001420484,0.0003596782,0.0009104426,0.01281042,0.05500631,0.4991184,0.0004659548,0.001520569,0.2654056],"study_design_scores_gemma":[0.0003614719,0.03507956,0.7511236,0.0001953254,0.0005941518,0.002341761,0.004986308,0.1212233,0.07943065,0.0007181629,0.003557501,0.0003882359],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974233,0.00005227855,0.002166837,0.0000119977,0.000005508002,0.00001136139,0.00005335105,0.00005182969,0.0002236841],"genre_scores_gemma":[0.9971866,0.00007584892,0.002031791,0.0000118292,0.000005208033,0.00001815153,0.0001032614,0.00001553468,0.0005517498],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001998755,"threshold_uncertainty_score":0.006686509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0260566062969532,"score_gpt":0.3032039278051022,"score_spread":0.277147321508149,"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."}}