{"id":"W4285064257","doi":"10.1007/978-3-030-03243-2_881-1","title":"Simplified Active Calibration","year":2020,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Calibration; Camera resectioning; Point (geometry); Artificial intelligence; Computer vision; Computer science; Camera auto-calibration; Focal length; Rotation (mathematics); Algorithm; Linear equation; Mathematics; Geometry; Optics; Physics; 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":[0.0002338625,0.001394662,0.0008473618,0.001081956,0.0005870683,0.001491857,0.001495729,0.001190336,0.07562274],"category_scores_gemma":[0.0007873031,0.0007322067,0.0006625513,0.001064488,0.0007356479,0.001894632,0.00166862,0.001894332,0.0565894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005373727,"about_ca_system_score_gemma":0.000510726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001162022,"about_ca_topic_score_gemma":0.001929792,"domain_scores_codex":[0.9996442,0.0000347786,0.000009158418,0.00009081641,0.0001974188,0.00002357418],"domain_scores_gemma":[0.9997736,0.00003662134,0.000008330122,0.00009780816,0.00007341347,0.00001029734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000491652,0.00003965898,0.00007773773,0.0002425999,0.00002179956,0.00008623751,0.00008839741,0.01110612,0.01563574,0.1901476,0.1388005,0.6437044],"study_design_scores_gemma":[0.000009368954,0.00002835589,0.0003729525,0.00008279891,0.00002534672,0.0005794052,0.00003766148,0.03583456,0.01225264,0.1099001,0.8408293,0.00004749402],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001130827,0.00421644,0.6344334,0.0004640376,0.001286045,0.00005652936,0.0004492094,0.004191921,0.3537716],"genre_scores_gemma":[0.03682861,0.003989601,0.2121797,0.0005887428,0.0005163591,0.0001117289,0.001634428,0.002077307,0.7420735],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07562274,"threshold_uncertainty_score":0.2529833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02857881614279534,"score_gpt":0.2624636124751673,"score_spread":0.2338847963323719,"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."}}