{"id":"W4395011868","doi":"10.3390/s24082662","title":"Using a Slit to Suppress Optical Aberrations in Laser Triangulation Sensors","year":2024,"lang":"en","type":"article","venue":"Sensors","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Rimouski","funders":"Université du Québec à Rimouski","keywords":"Triangulation; Lens (geology); Slit; Position (finance); Optics; Laser; Diffraction; Computer science; Computer vision; Artificial intelligence; Measure (data warehouse); Object (grammar); Image sensor; Table (database); Physics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002820731,0.0001084337,0.0001267544,0.0002691144,0.00003701599,0.000266079,0.0002205376,0.00006878081,0.00003666978],"category_scores_gemma":[0.0001312334,0.00009999674,0.0000508941,0.0005798401,0.00002311791,0.0003330498,0.00007322102,0.0001436094,0.0001201588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008710985,"about_ca_system_score_gemma":0.00003103043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003001431,"about_ca_topic_score_gemma":0.00002309086,"domain_scores_codex":[0.9989211,0.00005683456,0.0002437789,0.000328323,0.0002111794,0.0002388129],"domain_scores_gemma":[0.99951,0.00007640896,0.00001334217,0.00025696,0.00005172601,0.00009152096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000812162,0.0003634472,0.001034993,0.0001533054,0.00008228735,0.0003389244,0.01103657,0.02360741,0.2471657,0.6909671,0.004997086,0.02017193],"study_design_scores_gemma":[0.0001781824,0.0001545197,0.00176061,0.0002755762,0.0000112571,0.00001578132,0.0001083942,0.8931776,0.09592431,0.005852917,0.002186528,0.0003542647],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8994495,0.00003026776,0.08220164,0.002865176,0.0004693482,0.0003490916,0.000002707377,0.0004750156,0.01415722],"genre_scores_gemma":[0.9563404,0.000001347531,0.04310851,0.00008777704,0.00006514998,0.00001005007,9.940107e-7,0.000009003831,0.0003767735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8695703,"threshold_uncertainty_score":0.4077749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08362354508502286,"score_gpt":0.340852046472695,"score_spread":0.2572285013876721,"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."}}