{"id":"W2128518130","doi":"10.1109/plans.1994.303408","title":"High accuracy airborne GPS positioning: testing, data processing and results","year":2002,"lang":"en","type":"article","venue":"","topic":"GNSS positioning and interference","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"University of Calgary","keywords":"Remote sensing; Computer science; Initialization; Global Positioning System; Photogrammetry; Gps receiver; Flight test; Range (aeronautics); Real-time computing; Assisted GPS; Simulation; Artificial intelligence; Engineering; Geography; Aerospace engineering; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001110578,0.0005897527,0.0004228179,0.000808404,0.000400937,0.000682698,0.0006045454,0.000564633,0.002237285],"category_scores_gemma":[0.00386158,0.0001725433,0.0002512388,0.001456514,0.0004596935,0.0004596916,0.0004423336,0.0002673049,0.0007718116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004705906,"about_ca_system_score_gemma":0.0003037187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009222132,"about_ca_topic_score_gemma":0.003811764,"domain_scores_codex":[0.9977769,0.000509555,0.0001497949,0.0002028933,0.001163922,0.0001969835],"domain_scores_gemma":[0.9969471,0.001330144,0.0001297061,0.0004309479,0.001076989,0.00008512851],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003537721,0.000799464,0.07042632,0.0007202323,0.0002207567,0.00166194,0.001502927,0.3565548,0.1122017,0.002305529,0.004835717,0.4452328],"study_design_scores_gemma":[0.0006575335,0.005373571,0.1290744,0.00005446675,0.0002690296,0.001057898,0.001185454,0.4659958,0.3818595,0.001549579,0.01272772,0.0001951255],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9459159,0.0001434987,0.04504782,0.0001416822,0.0000455563,0.0001652311,0.001391837,0.002563045,0.004585514],"genre_scores_gemma":[0.9842216,0.00004785417,0.01349344,0.00002286151,0.00001213497,0.00004037426,0.0009031766,0.0001310586,0.001127501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009222132,"threshold_uncertainty_score":0.01833689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06123026327542463,"score_gpt":0.2529161856348014,"score_spread":0.1916859223593768,"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."}}