{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001224325,0.0004760541,0.0006526576,0.0007714498,0.0005806957,0.001051297,0.001438616,0.001388219,0.001435411],"category_scores_gemma":[0.005344009,0.0006013901,0.0004694028,0.001147177,0.0008014686,0.001922393,0.0009680571,0.0007980586,0.0007327509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008097374,"about_ca_system_score_gemma":0.001060327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001532645,"about_ca_topic_score_gemma":0.002493738,"domain_scores_codex":[0.9977574,0.0002618447,0.0001897199,0.0003929449,0.001299772,0.0000983039],"domain_scores_gemma":[0.9932455,0.002340495,0.001191156,0.001167608,0.001892492,0.0001627353],"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":[0.0005217054,0.0001589646,0.007978321,0.0006462012,0.00009232578,0.0004551063,0.0004740567,0.01147157,0.8212066,0.007022636,0.001347646,0.1486249],"study_design_scores_gemma":[0.0000674637,0.001236237,0.01043919,0.00007872802,0.00009744,0.002154576,0.0001934672,0.1331712,0.8343617,0.00258896,0.0154666,0.0001445433],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07929525,0.0007846887,0.9161925,0.0001754593,0.0001739543,0.00008490193,0.0001685865,0.001438505,0.001686147],"genre_scores_gemma":[0.2747791,0.0003644916,0.7226236,0.0002171573,0.00005061524,0.00009796003,0.0002184797,0.0001524058,0.001496181],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001532645,"threshold_uncertainty_score":0.006474912,"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."}}