{"id":"W1648355160","doi":"10.1007/978-3-540-32256-6_53","title":"Optimizing Precision of Self-Localization in the Simulated Robotics Soccer","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Cartesian coordinate system; Kalman filter; Orientation (vector space); Artificial intelligence; Heuristic; Robotics; Computer vision; Robot; 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":[0.0004904947,0.0005525182,0.0007032077,0.0002587837,0.0002896164,0.0006996335,0.000627418,0.0008013891,0.001544084],"category_scores_gemma":[0.001999523,0.000501967,0.0002898882,0.0003549407,0.0006194627,0.0005805132,0.000945624,0.0004512971,0.0002328011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004854116,"about_ca_system_score_gemma":0.0006855204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004049258,"about_ca_topic_score_gemma":0.003153922,"domain_scores_codex":[0.9997835,0.00006242002,0.00001015099,0.00004056859,0.00007044168,0.00003300219],"domain_scores_gemma":[0.9994705,0.0002974236,0.00005687803,0.00005466992,0.00009627197,0.00002431679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001012632,0.00001848116,0.0003220558,0.00003524691,0.00001612283,0.0000176963,0.00003942309,0.9663861,0.004007583,0.00263942,0.0002952288,0.0261214],"study_design_scores_gemma":[0.00001216894,0.00006273892,0.0001870214,0.000005278078,0.000005400503,0.00001549681,0.00001006206,0.9957124,0.002309445,0.00147416,0.0002006663,0.000005144269],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2132506,0.0004057668,0.7786582,0.0001908279,0.0000430808,0.0000308732,0.00004805782,0.0005162525,0.006856316],"genre_scores_gemma":[0.9685419,0.00007481455,0.02964976,0.00001432737,0.000007910991,0.00001989608,0.00002365879,0.0000641197,0.001603555],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004049258,"threshold_uncertainty_score":0.008051395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01738181153946062,"score_gpt":0.2783587371033082,"score_spread":0.2609769255638476,"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."}}