{"id":"W4414271693","doi":"10.1109/tmech.2025.3602812","title":"Systematic Error Correction in Robotic-OCT Inspection of Hard-to-Reach Industrial Parts","year":2025,"lang":"en","type":"article","venue":"IEEE/ASME Transactions on Mechatronics","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Liaoning Revitalization Talents Program","keywords":"Completeness (order theory); Distortion (music); Systematic error; Error detection and correction; Rotation (mathematics); Point cloud; Coherence (philosophical gambling strategy); Point (geometry)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007037327,0.0002886568,0.0006527993,0.001138836,0.0001471922,0.00005028374,0.0001431624,0.0004643195,0.00002360479],"category_scores_gemma":[0.00006013899,0.0003003848,0.0002174188,0.001560029,0.00001861095,0.0001879132,0.000002433695,0.0007378212,0.00007281773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008045803,"about_ca_system_score_gemma":0.000102122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002672783,"about_ca_topic_score_gemma":0.0004473935,"domain_scores_codex":[0.9977969,0.0001963465,0.0009814363,0.0003321557,0.0003433128,0.0003498345],"domain_scores_gemma":[0.9990972,0.0001696525,0.0001178613,0.0004292004,0.00009675572,0.00008938448],"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":[0.0001309799,0.000128145,0.00002372152,0.0008757389,0.0001327437,0.000001614179,0.0002317888,0.9895251,0.004391038,0.0001639118,0.0009699408,0.003425214],"study_design_scores_gemma":[0.005242421,0.001169593,0.000255419,0.01308536,0.0005556211,0.00003924071,0.002431258,0.7904559,0.1838945,0.0001669719,0.001588426,0.001115248],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1751908,0.0001291274,0.7985743,0.00007534171,0.02202966,0.002162814,0.00002353515,0.0009523858,0.0008620719],"genre_scores_gemma":[0.9988605,0.00002308286,0.0001835663,0.0000175559,0.0001163117,0.0002390269,0.00000382059,0.00004170379,0.0005143828],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8236697,"threshold_uncertainty_score":0.9999448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02745429770535035,"score_gpt":0.2526846237762994,"score_spread":0.225230326070949,"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."}}