{"id":"W2083847778","doi":"10.1016/j.patcog.2007.12.010","title":"Camera self-calibration from bivariate polynomials derived from Kruppa's equations","year":2008,"lang":"en","type":"article","venue":"Pattern Recognition","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Bivariate analysis; Mathematics; Scale (ratio); Polynomial; Calibration; Nonlinear system; Set (abstract data type); Linear equation; Least-squares function approximation; Applied mathematics; Homotopy; Constant (computer programming); Mathematical analysis; Computer science; Statistics; Pure 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":[0.0005957829,0.0006120536,0.0006719614,0.000676076,0.0003700337,0.0008402578,0.0008095129,0.0007713271,0.001798057],"category_scores_gemma":[0.003720711,0.0005685694,0.0007946471,0.001167693,0.0008407704,0.00165497,0.001060368,0.001945829,0.0006007144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006316503,"about_ca_system_score_gemma":0.0007473051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00426244,"about_ca_topic_score_gemma":0.004685085,"domain_scores_codex":[0.9995803,0.0001031666,0.00002112017,0.00009692911,0.0001601858,0.00003830311],"domain_scores_gemma":[0.9992962,0.0003032967,0.0001104184,0.0001014092,0.0001666818,0.00002204901],"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":[0.00006558742,0.00003044081,0.001580283,0.0002547559,0.00007558375,0.0002696397,0.0004354297,0.4134284,0.01244262,0.4351285,0.003111932,0.1331768],"study_design_scores_gemma":[0.000007157093,0.0000131605,0.0006177716,0.00002578475,0.0000185261,0.0001704096,0.00003345914,0.9508745,0.00246956,0.04269391,0.003041417,0.00003428983],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01041085,0.0003766357,0.9861187,0.00007926821,0.00004627988,0.00001573034,0.00004013548,0.00008586588,0.002826657],"genre_scores_gemma":[0.6427475,0.002236207,0.3444729,0.0001098272,0.00009111399,0.00007700371,0.0002267876,0.0002971264,0.009741421],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00426244,"threshold_uncertainty_score":0.008475304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04330799229138021,"score_gpt":0.2603407816562544,"score_spread":0.2170327893648742,"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."}}