{"id":"W2414779538","doi":"10.1109/icra.2016.7487630","title":"Elasto-geometrical calibration of an industrial robot under multidirectional external loads using a laser tracker","year":2016,"lang":"en","type":"article","venue":"","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Robot calibration; Robot; Laser tracker; Calibration; Robot end effector; Position (finance); Industrial robot; Control theory (sociology); Robustness (evolution); Kinematics; Noise (video); Engineering; Robot kinematics; Computer science; Artificial intelligence; Computer vision; Laser; Mathematics; Mobile robot; Physics; Optics","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":[0.0001081337,0.0001091024,0.0001405797,0.000133191,0.00003256514,0.00002233434,0.00006486718,0.0001514009,0.0005655158],"category_scores_gemma":[0.00002810339,0.00007779001,0.00004657226,0.0002092024,0.00002079165,0.000290221,0.00001474502,0.00008385601,0.000004824918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000766513,"about_ca_system_score_gemma":0.0000274358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006496056,"about_ca_topic_score_gemma":0.000023635,"domain_scores_codex":[0.9992157,0.00002315281,0.0002551997,0.0001350238,0.000208963,0.0001619419],"domain_scores_gemma":[0.9996539,0.00006686114,0.0000331861,0.000117534,0.00003350442,0.00009501277],"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":[0.00002536788,0.00005793155,0.000291888,0.000004311215,0.00002192028,0.000001934903,0.00001037214,0.9289644,0.05957954,0.001654435,0.00004910983,0.009338776],"study_design_scores_gemma":[0.0008918013,0.0000630178,0.0006754473,0.00002520392,0.00001509567,0.00001559378,0.00001629694,0.9792941,0.01803886,0.0008024775,0.00001206434,0.0001500584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.228191,0.000005155495,0.7711,0.000014707,0.0003902612,0.00005734664,0.00000712674,0.00007785347,0.0001565233],"genre_scores_gemma":[0.8782562,0.000003853954,0.1210412,0.00001596932,0.0002709301,0.000002892884,0.000003993451,0.0000271031,0.0003778322],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6500652,"threshold_uncertainty_score":0.6192002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04054493932913595,"score_gpt":0.2423167277203521,"score_spread":0.2017717883912162,"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."}}