{"id":"W2157405987","doi":"10.1109/cvpr.1993.341084","title":"Active calibration: alternative strategy and analysis","year":2002,"lang":"en","type":"article","venue":"","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Calibration; Noise (video); Artificial intelligence; Computer vision; Image (mathematics); Mathematics; Statistics","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":[0.001104418,0.00137516,0.0007401694,0.002049577,0.0004590816,0.00241665,0.00220837,0.001719965,0.009436254],"category_scores_gemma":[0.002966292,0.0004744726,0.001304116,0.001792104,0.001507146,0.002756634,0.001690818,0.001786754,0.003202654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009100452,"about_ca_system_score_gemma":0.0005570764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001529366,"about_ca_topic_score_gemma":0.001003546,"domain_scores_codex":[0.9989466,0.0002363583,0.0000450178,0.000196871,0.0005045244,0.00007056129],"domain_scores_gemma":[0.9989128,0.0003841107,0.00009808034,0.0001913399,0.0003716599,0.00004192422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006932109,0.00007725688,0.0004662325,0.0003347411,0.00009014621,0.0001701837,0.0002413501,0.08246531,0.009464995,0.6891085,0.005415561,0.2120964],"study_design_scores_gemma":[0.00001034028,0.00006043724,0.000289483,0.00007061719,0.00003549728,0.0002803383,0.00005227091,0.8203232,0.004894971,0.1542813,0.01965666,0.00004487727],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0010053,0.0005638108,0.9946035,0.00006902213,0.00004956282,0.00001219972,0.00001354773,0.00009422329,0.00358884],"genre_scores_gemma":[0.2642522,0.005591097,0.6904048,0.000575427,0.0006969011,0.0003362885,0.0003391372,0.0006184561,0.03718566],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009436254,"threshold_uncertainty_score":0.03156739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07170889210100308,"score_gpt":0.2766359611305012,"score_spread":0.2049270690294981,"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."}}