{"id":"W1974230855","doi":"10.1109/jsyst.2011.2173622","title":"Robust Positioning Systems in the Presence of Outliers Under Weak GPS Signal Conditions","year":2011,"lang":"en","type":"article","venue":"IEEE Systems Journal","topic":"Water Systems and Optimization","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Outlier; Global Positioning System; Robustness (evolution); Ranging; Computer science; Anomaly detection; GPS signals; Algorithm; Assisted GPS; Real-time computing; Data mining; Artificial intelligence; Telecommunications","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":[0.001691076,0.0008435324,0.001222239,0.0006662472,0.0003849871,0.000908807,0.001031538,0.001266617,0.0005434779],"category_scores_gemma":[0.009545477,0.0003843881,0.0004772191,0.0009416618,0.0007602039,0.001411449,0.001530084,0.001030124,0.0003900875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002986948,"about_ca_system_score_gemma":0.0003983306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000814627,"about_ca_topic_score_gemma":0.0004862232,"domain_scores_codex":[0.9984784,0.0004726813,0.000114638,0.0002585453,0.0005589075,0.0001168861],"domain_scores_gemma":[0.9958687,0.00199687,0.0009890336,0.0005679677,0.0005109709,0.00006652928],"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":[0.0004157216,0.00003475885,0.001854695,0.0002287436,0.0001843906,0.00053333,0.0002255227,0.7990973,0.02450804,0.01744471,0.0008160093,0.1546567],"study_design_scores_gemma":[0.00003060126,0.0001690761,0.0009055327,0.00001538972,0.00004157959,0.0002478606,0.00004034362,0.9752052,0.0123886,0.008827941,0.002086114,0.00004180998],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02028958,0.0003570464,0.9785053,0.00009480306,0.00004022584,0.00001217899,0.00002121296,0.0002904057,0.0003891884],"genre_scores_gemma":[0.7247183,0.0006566727,0.2727873,0.00008597135,0.0001391137,0.00006988461,0.0001373804,0.00009246921,0.001312999],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001691076,"threshold_uncertainty_score":0.008943379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03905575105447048,"score_gpt":0.2102867206286351,"score_spread":0.1712309695741646,"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."}}