{"id":"W2897095722","doi":"10.3390/s18103380","title":"Self-Calibration of an Industrial Robot Using a Novel Affordable 3D Measuring Device","year":2018,"lang":"en","type":"article","venue":"Sensors","topic":"Advanced Measurement and Metrology Techniques","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Laser tracker; Calibration; Robot; Robot calibration; Industrial robot; Simulation; Computer science; Position (finance); Accuracy and precision; Engineering; Artificial intelligence; Computer vision; Robot kinematics; Mobile robot; Laser; Mathematics; Optics; Physics","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":[0.001180808,0.0006731033,0.000679085,0.0007624919,0.0002095542,0.0006423065,0.001459081,0.0008375967,0.001540975],"category_scores_gemma":[0.002155772,0.0003743111,0.000453758,0.0005471006,0.0005119091,0.0007104333,0.001030253,0.0005181123,0.0005713949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003364601,"about_ca_system_score_gemma":0.0005230316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003428691,"about_ca_topic_score_gemma":0.0003822106,"domain_scores_codex":[0.9981268,0.0002299356,0.00008291808,0.0003234072,0.001164473,0.00007238287],"domain_scores_gemma":[0.9989076,0.0002945184,0.0002507493,0.000309772,0.0001955232,0.0000417959],"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":[0.0002275242,0.0001487786,0.004795296,0.0005472781,0.00004912209,0.0003502741,0.0003885405,0.01216591,0.7710133,0.004105876,0.001388746,0.2048195],"study_design_scores_gemma":[0.0001607141,0.00219526,0.02431869,0.0001433031,0.0001810856,0.003454325,0.0001630452,0.1957565,0.7319564,0.001391691,0.04003923,0.0002398216],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0873021,0.0003458273,0.9079413,0.0001196822,0.0001366029,0.0001312157,0.0000838975,0.001767454,0.002171899],"genre_scores_gemma":[0.4910682,0.0002554938,0.5059074,0.0001132155,0.00004957012,0.000206585,0.0001064877,0.00007537206,0.00221766],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001540975,"threshold_uncertainty_score":0.006244838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08794335055564695,"score_gpt":0.2709937115238569,"score_spread":0.18305036096821,"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."}}