{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004489006,0.0003424553,0.0005614333,0.0001680578,0.00006437519,0.0001597106,0.001526006,0.0001881443,0.000005094407],"category_scores_gemma":[0.002738464,0.0002809883,0.0004205637,0.0003699904,0.0002255396,0.001314905,0.0002171622,0.0002709515,0.000001049838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000374243,"about_ca_system_score_gemma":0.00009421233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002211921,"about_ca_topic_score_gemma":4.776601e-7,"domain_scores_codex":[0.9967945,1.955112e-7,0.000894549,0.000484615,0.001403688,0.0004225032],"domain_scores_gemma":[0.9924251,0.0004864553,0.000636816,0.0001149812,0.006169437,0.0001671873],"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":[0.0003795949,0.0002111288,0.0004110028,0.0005286601,0.0005302424,6.428533e-8,0.000637824,0.00007438633,0.3345522,0.656836,0.002014406,0.003824529],"study_design_scores_gemma":[0.005206176,0.002163765,0.0004226514,0.0009953922,0.0006888846,0.00001700046,0.001451145,0.7581515,0.2160523,0.01198357,0.002136541,0.0007310926],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9530737,0.0006875795,0.03242406,0.002385579,0.00139546,0.002108275,0.00005173537,0.0002411578,0.007632483],"genre_scores_gemma":[0.3572633,0.00001649782,0.6419084,0.00002860835,0.0003101006,0.0003859856,0.00001004166,0.00004189196,0.00003515518],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7580771,"threshold_uncertainty_score":0.9999642,"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."}}