{"id":"W2023198851","doi":"10.1155/2014/548083","title":"A Direct Attitude Determination Approach Based on GPS Double-Difference Carrier Phase Measurements","year":2014,"lang":"en","type":"article","venue":"Journal of Applied Mathematics","topic":"GNSS positioning and interference","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"National Natural Science Foundation of China","keywords":"Global Positioning System; Reference frame; Position (finance); Frame (networking); Matrix (chemical analysis); Computer science; Phase (matter); Mathematics; Algorithm; Control theory (sociology); Artificial intelligence; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0004269244,0.0001515517,0.0002647931,0.0001252412,0.00004532626,0.00005810291,0.0001853313,0.00006258456,0.00001280957],"category_scores_gemma":[0.00003531026,0.0001241766,0.00006772003,0.00008100089,0.00001890544,0.00004992606,0.000008112071,0.0001904328,0.0000110593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008455779,"about_ca_system_score_gemma":0.0000190375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.559245e-7,"about_ca_topic_score_gemma":2.536068e-7,"domain_scores_codex":[0.998969,0.000009374337,0.0003968827,0.00008331821,0.000395256,0.000146144],"domain_scores_gemma":[0.999366,0.00006435488,0.000178294,0.0001811188,0.0001270016,0.00008322118],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009801118,0.004803727,0.0000870383,0.004070608,0.0006076712,0.00001018766,0.01028062,0.3887751,0.4837464,0.01192493,0.004699368,0.09001417],"study_design_scores_gemma":[0.004096573,0.0004197131,0.00005233059,0.0004824236,0.0001429097,0.00002424673,0.0001064959,0.7864419,0.2064714,0.0011015,0.0003123399,0.000348232],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.183593,0.00001826705,0.6264786,0.00001817229,0.0002544879,0.000210222,0.000005915484,0.0001004093,0.1893209],"genre_scores_gemma":[0.9562436,0.0000020438,0.04358164,0.00003377286,0.0000869576,0.00001207237,0.000002921203,0.00001941459,0.00001756989],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7726506,"threshold_uncertainty_score":0.5063774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04085268555948363,"score_gpt":0.2656541834508644,"score_spread":0.2248014978913808,"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."}}