{"id":"W2063368546","doi":"10.1109/smc.2014.6974193","title":"An efficient method of correcting position mismatch between a haptic device and a robot-assisted tool","year":2014,"lang":"en","type":"article","venue":"","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Workspace; Haptic technology; Computer science; Robot; Controller (irrigation); Orientation (vector space); Position (finance); Robot end effector; Computation; Imaging phantom; Simulation; Artificial intelligence; Computer vision; Algorithm; Mathematics","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":[0.0001779225,0.0000691293,0.0001212373,0.00003760849,0.00004201096,0.00002178504,0.00004929549,0.00003920776,0.000007343129],"category_scores_gemma":[0.0000140044,0.00006684182,0.00001860197,0.000115901,0.000008262382,0.00002395238,0.0000101921,0.00005087074,0.000003634986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001377725,"about_ca_system_score_gemma":0.000003266563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000511696,"about_ca_topic_score_gemma":0.000007958767,"domain_scores_codex":[0.9995652,0.00002075093,0.0001554216,0.0001039378,0.00006027997,0.00009441599],"domain_scores_gemma":[0.9995769,0.0001819499,0.00002510314,0.0001393604,0.00003245969,0.00004419828],"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":[0.000002930118,0.00007430343,0.005199428,0.0001648197,0.00005134771,2.66294e-7,0.0006487315,0.518241,0.1772056,0.003056455,0.00004496986,0.2953101],"study_design_scores_gemma":[0.0001305125,0.00002573796,0.045351,0.00002082837,0.00003942486,0.000006770156,0.00007224662,0.9435427,0.01059491,0.00008773247,0.00003263216,0.0000954733],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3904102,0.000007402502,0.6088974,0.00002502499,0.00001801684,0.0000658061,0.000001177001,0.00008645433,0.0004884375],"genre_scores_gemma":[0.8389526,4.876469e-7,0.1609712,0.00001443654,0.00002590948,0.000008411391,0.000006846198,0.00001137449,0.000008677162],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4485424,"threshold_uncertainty_score":0.272573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01542744540509084,"score_gpt":0.2735496364223614,"score_spread":0.2581221910172705,"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."}}