{"id":"W1719590446","doi":"10.5772/60881","title":"Metrological Evaluation of a Novel Medical Robot and Its Kinematic Calibration","year":2015,"lang":"en","type":"article","venue":"International Journal of Advanced Robotic Systems","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Calibration; Robot; Kinematics; Repeatability; Robot calibration; Computer vision; Metrology; Artificial intelligence; Process (computing); Identification (biology); Position (finance); Robot kinematics; Simulation; Mobile robot; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00130785,0.0005460368,0.0005021474,0.0006654213,0.0002822886,0.0004773226,0.000625708,0.001001068,0.000873371],"category_scores_gemma":[0.003734514,0.0002666215,0.0002554566,0.000487289,0.0004844827,0.0005794184,0.0005030409,0.0003291809,0.0003828685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002666159,"about_ca_system_score_gemma":0.0004251066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003577106,"about_ca_topic_score_gemma":0.0002699237,"domain_scores_codex":[0.9985759,0.0002587913,0.00006892824,0.000250382,0.0007860157,0.00006001093],"domain_scores_gemma":[0.9985672,0.0003956162,0.0002533204,0.0002136834,0.000526047,0.00004408404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004970418,0.0001674675,0.005802861,0.0004778405,0.00005285392,0.0003955775,0.0004155851,0.01262126,0.8678792,0.001597007,0.0006223044,0.109471],"study_design_scores_gemma":[0.00008484652,0.003874725,0.02472555,0.00007097892,0.0001307393,0.003965906,0.0002430647,0.2219587,0.7317117,0.0007943321,0.01231103,0.0001285039],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4756584,0.001241627,0.5158855,0.0003777826,0.0002780071,0.0002081766,0.0001393398,0.001578814,0.004632281],"genre_scores_gemma":[0.8999207,0.000265612,0.09826791,0.0000594328,0.00003047984,0.0000708004,0.00005780621,0.00003777001,0.001289483],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00130785,"threshold_uncertainty_score":0.006916642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06839364783470707,"score_gpt":0.3269774493923954,"score_spread":0.2585838015576883,"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."}}