{"id":"W2974013300","doi":"10.48550/arxiv.1909.08537","title":"Visual Measurement Integrity Monitoring for UAV Localization","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Receiver autonomous integrity monitoring; GNSS applications; Computer science; Metric (unit); Real-time computing; Computer vision; Global Positioning System; Artificial intelligence; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002243409,0.0002856937,0.000283052,0.0001788934,0.00008220258,0.00006106111,0.0002440864,0.0003721161,0.0000115519],"category_scores_gemma":[0.00004431099,0.0003562231,0.0001601753,0.0002020853,0.00002496436,0.000102486,0.0001127283,0.0003877702,0.00002991088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006683607,"about_ca_system_score_gemma":0.00007851695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004864134,"about_ca_topic_score_gemma":0.0000166157,"domain_scores_codex":[0.9988928,0.00004023077,0.0002093387,0.0004638102,0.0001261939,0.0002676488],"domain_scores_gemma":[0.9990634,0.0000377141,0.00008191419,0.0003676567,0.0003557759,0.00009353177],"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":[0.00002290049,0.00003257141,0.003937285,0.0004115887,0.00009346226,0.000005217621,0.000048842,0.9923444,0.0001714891,0.002458244,0.0002336428,0.0002403619],"study_design_scores_gemma":[0.0004112039,0.00003548729,0.0003779789,0.0002107639,0.0001097204,2.67796e-7,0.00007664321,0.9944349,0.001936895,0.001477631,0.0005566786,0.0003718569],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08395272,0.00008956954,0.9129463,0.000007712519,0.001737495,0.0005215898,0.00001655888,0.0002847488,0.0004432298],"genre_scores_gemma":[0.9988887,0.0001986585,0.0004003412,0.000009931334,0.0002108598,0.000002199555,0.00008418498,0.00005993899,0.0001451371],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.914936,"threshold_uncertainty_score":0.999889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1138720901818795,"score_gpt":0.2026591525370832,"score_spread":0.08878706235520371,"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."}}