{"id":"W2955345547","doi":"10.1117/12.2526434","title":"Ultraprecise micromachining of retroreflective structures","year":2019,"lang":"en","type":"article","venue":"","topic":"Surface Roughness and Optical Measurements","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Retroreflector; Corner reflector; Mechanical engineering; Fabrication; Cube (algebra); Automotive industry; Point (geometry); Kinematics; Engineering drawing; Computer science; Optics; Engineering; Geometry; Aerospace engineering; Physics; Laser","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":[0.00004969608,0.00007182722,0.0001280166,0.00003085466,0.000008068399,0.00000419556,0.00007019192,0.00003635459,0.0006525561],"category_scores_gemma":[0.00001414878,0.00005573107,0.00002686064,0.00008321298,0.00001362575,0.00004886095,0.000006921403,0.00006549673,0.00003024965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001661926,"about_ca_system_score_gemma":0.000002614913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001245675,"about_ca_topic_score_gemma":0.000002149335,"domain_scores_codex":[0.9995902,0.000007528253,0.0001122742,0.00007700816,0.0001045438,0.0001084256],"domain_scores_gemma":[0.9997885,0.00003385502,0.00001147613,0.0001142947,0.00002589674,0.0000260025],"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":[0.00001987023,0.00001030529,0.03568594,0.00009101276,0.00009083014,5.122813e-7,0.0004839424,0.009651563,0.9390231,0.005477461,0.0003066419,0.009158785],"study_design_scores_gemma":[0.0008910606,0.0001403311,0.1414561,0.00008252424,0.00002201121,0.000002022563,0.0003856735,0.00817444,0.8423695,0.005064217,0.001058324,0.0003538213],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8910594,0.0001380686,0.0007638577,0.00000398901,0.0002619606,0.0000709057,0.000001536749,0.00007353325,0.1076268],"genre_scores_gemma":[0.9974437,0.000006863407,0.002420377,0.000008125689,0.00001348704,0.000001165632,7.991282e-7,0.00001255256,0.00009297011],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1075338,"threshold_uncertainty_score":0.7145031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007009725221876823,"score_gpt":0.2006119196987378,"score_spread":0.193602194476861,"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."}}