{"id":"W2056807004","doi":"10.1364/ao.53.002822","title":"Virtual camera calibration using optical design software","year":2014,"lang":"en","type":"article","venue":"Applied Optics","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Calibration; Computer science; Software; Process (computing); Optics; Lens (geology); Camera resectioning; Remote sensing; Computer vision; Physics","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":[0.001193917,0.0008954625,0.0005342921,0.00150768,0.0004564877,0.00154782,0.001370004,0.0006905849,0.01664993],"category_scores_gemma":[0.003538671,0.0007688986,0.0006366343,0.0005587629,0.0004195261,0.001118573,0.001208697,0.001021951,0.002700639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006307915,"about_ca_system_score_gemma":0.0009736351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001057634,"about_ca_topic_score_gemma":0.001177158,"domain_scores_codex":[0.9990922,0.0001185802,0.00005501831,0.0001812462,0.0005032026,0.00004976225],"domain_scores_gemma":[0.998607,0.0004205986,0.0001319646,0.0002371025,0.0005567588,0.00004659213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000512371,0.0001617883,0.00239719,0.0007226468,0.0001971471,0.0002823575,0.0003916903,0.064335,0.1072227,0.02189378,0.02034836,0.7815349],"study_design_scores_gemma":[0.0002135822,0.0003446577,0.002031824,0.0001386971,0.0001080961,0.0009835419,0.0001220638,0.6659319,0.1766571,0.01219473,0.1410927,0.0001809931],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003064087,0.0000853385,0.9843493,0.00003119605,0.00005523405,0.00008068645,0.00007900993,0.01007931,0.002175879],"genre_scores_gemma":[0.1506865,0.0002901548,0.8374297,0.000109219,0.00003197532,0.0005744528,0.0004943853,0.003477589,0.006906028],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01664993,"threshold_uncertainty_score":0.05569959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05193494749280031,"score_gpt":0.2586492590147945,"score_spread":0.2067143115219942,"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."}}