{"id":"W1469842922","doi":"10.1117/12.2179591","title":"Single-plane versus three-plane methods for relative range error evaluation of medium-range 3D imaging systems","year":2015,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Range (aeronautics); Plane (geometry); Context (archaeology); Optics; Approximation error; Metric (unit); Image plane; Computer science; Computer vision; Algorithm; Geometry; Physics; Mathematics; Materials science; Engineering; Image (mathematics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004041951,0.001031828,0.000657351,0.002678711,0.0003605211,0.00155829,0.001429373,0.0007930917,0.001718434],"category_scores_gemma":[0.01074706,0.0003485393,0.0005640445,0.001658276,0.0006632064,0.001557612,0.001667729,0.0009355391,0.0006825455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005198256,"about_ca_system_score_gemma":0.0006362646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007985472,"about_ca_topic_score_gemma":0.001609307,"domain_scores_codex":[0.9954302,0.000953525,0.0002594562,0.000424603,0.002816541,0.0001156851],"domain_scores_gemma":[0.9889358,0.004655313,0.00193234,0.001551122,0.0027776,0.0001479034],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007712581,0.0002986448,0.01151805,0.001560782,0.0002939413,0.0001668213,0.001118576,0.1238788,0.218929,0.02701187,0.002080359,0.612372],"study_design_scores_gemma":[0.00004951004,0.0005772552,0.01152228,0.0001651642,0.0001119762,0.001053203,0.0003755251,0.641001,0.3305712,0.004755753,0.009489198,0.0003278466],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01655071,0.0006415716,0.9807358,0.00003511086,0.00003962167,0.00005492039,0.00006404973,0.0007395941,0.001138504],"genre_scores_gemma":[0.1297494,0.0004345545,0.8685954,0.00002623492,0.00001936524,0.0001132065,0.000133698,0.0002431247,0.0006850984],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004041951,"threshold_uncertainty_score":0.02137613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08514346979286802,"score_gpt":0.3234667995094055,"score_spread":0.2383233297165375,"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."}}