{"id":"W2160030138","doi":"10.1109/tmech.2008.924118","title":"Human–Machine Interface for Robotic Surgery and Stereotaxy","year":2008,"lang":"en","type":"article","venue":"IEEE/ASME Transactions on Mechatronics","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"Foothills Medical Centre; University of Calgary","funders":"","keywords":"Workstation; Haptic technology; Stereoscopy; Interface (matter); Computer science; Human–computer interaction; Robot; Telerobotics; Component (thermodynamics); Teleoperation; Artificial intelligence; Embedded system; Operating system; Mobile robot","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":[0.0007170355,0.0005897813,0.0004796451,0.0005289486,0.0003130139,0.001146701,0.0009862526,0.001560835,0.03584875],"category_scores_gemma":[0.001622605,0.0001586436,0.0003503195,0.0006383875,0.000718614,0.001073059,0.0007638176,0.0008853307,0.009829331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003846865,"about_ca_system_score_gemma":0.000357992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009365108,"about_ca_topic_score_gemma":0.00103565,"domain_scores_codex":[0.9991078,0.0002267729,0.00006324145,0.000119018,0.000433447,0.00004973151],"domain_scores_gemma":[0.9993337,0.0002547831,0.00005546376,0.00009281594,0.0002184498,0.00004465419],"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":[0.0003379221,0.0001063722,0.0005769528,0.00119595,0.00006150745,0.0007028554,0.0003784484,0.003416807,0.05155506,0.06656162,0.1438503,0.7312563],"study_design_scores_gemma":[0.00005504608,0.0003414985,0.002613723,0.0002753402,0.00004425254,0.00184706,0.0001311516,0.03975223,0.01433014,0.03651242,0.9040046,0.00009255888],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009000133,0.0364841,0.7854303,0.004293328,0.003250766,0.0004586674,0.0007548072,0.009755903,0.150572],"genre_scores_gemma":[0.2985923,0.02087141,0.4725512,0.004438363,0.002535863,0.001120236,0.002897222,0.000894371,0.196099],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03584875,"threshold_uncertainty_score":0.119926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02982080708264355,"score_gpt":0.2459171659129028,"score_spread":0.2160963588302593,"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."}}