{"id":"W1994064153","doi":"10.1007/s001380000043","title":"Machine vision system for curved surface inspection","year":2000,"lang":"en","type":"article","venue":"Machine Vision and Applications","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; National Research Council Canada","funders":"","keywords":"Computer vision; Artificial intelligence; Structured light; Curvature; Computer science; Triangulation; Geodetic datum; Linearity; System of measurement; Mathematics; Engineering; Geology; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001447077,0.0001719611,0.0001589445,0.00005897276,0.0004233888,0.00009944098,0.0001352744,0.00007795628,0.00005534856],"category_scores_gemma":[0.000002489507,0.0001548568,0.0000527074,0.0002841277,0.00004000189,0.0001214739,0.00002086121,0.0001240891,0.00005382353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004309453,"about_ca_system_score_gemma":0.000006112176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003525622,"about_ca_topic_score_gemma":0.000008335772,"domain_scores_codex":[0.9992036,0.00001122531,0.0002533898,0.0002692862,0.00009224986,0.0001702604],"domain_scores_gemma":[0.9994913,0.00003904534,0.00003419651,0.0003047389,0.00004575423,0.00008497862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003078612,0.0002064972,0.0001333675,0.0005081893,0.00002617747,3.688527e-7,0.0001064849,0.005506605,0.02850127,0.01687617,0.007680087,0.940424],"study_design_scores_gemma":[0.0003723467,0.00004493761,0.0003344989,0.00004421551,0.00002365495,0.00001315766,0.00001846957,0.6131567,0.003342784,0.000964452,0.3814583,0.0002264369],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0154478,0.001990323,0.9626124,0.0006786764,0.00004858499,0.001566187,0.0002277683,0.003717679,0.01371056],"genre_scores_gemma":[0.9777942,0.0004414647,0.02014967,0.00005042783,0.00008614222,0.0005700681,0.0001867793,0.00005097833,0.0006703181],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9623464,"threshold_uncertainty_score":0.6314876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006244543806893696,"score_gpt":0.2663803815078344,"score_spread":0.2601358377009407,"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."}}