{"id":"W2527482605","doi":"","title":"AIRBORNE KINEMATIC POSITIONING USING PRECISE POINT POSITIONING METHODOLOGY","year":2019,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Precise Point Positioning; Kinematics; Geodesy; Geography; Remote sensing; Point (geometry); Computer science; Global Positioning System; GNSS applications; Cartography; Mathematics; Physics; Geometry; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002679789,0.0001403667,0.0002360305,0.0001013132,0.00008023828,0.00004288443,0.0001140524,0.00008979656,0.0005189963],"category_scores_gemma":[0.00008051145,0.0001436808,0.00006521779,0.0001817577,0.0000164193,0.0001966435,0.00003329165,0.0001325296,0.0003771119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008434329,"about_ca_system_score_gemma":0.000007924763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003208125,"about_ca_topic_score_gemma":0.000001820493,"domain_scores_codex":[0.999047,0.00008685049,0.0003160963,0.0001402154,0.0001400703,0.0002697532],"domain_scores_gemma":[0.9993865,0.0001728556,0.00004849562,0.0002899907,0.0000458688,0.00005623436],"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":[0.00002382355,0.0000318446,0.0002236679,0.0005812367,0.0001103982,0.00001303757,0.001594782,0.4334646,0.5561856,0.004577192,0.0002618656,0.002931993],"study_design_scores_gemma":[0.000474019,0.00006237337,0.002682011,0.0004020283,0.0000878519,0.0001208138,0.0001625455,0.9383672,0.04967387,0.007581097,0.00004323925,0.0003429806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8898562,0.00009014091,0.1014013,0.0001000292,0.0004151314,0.0002842772,0.00000382398,0.0003063358,0.007542735],"genre_scores_gemma":[0.8890869,0.000002938034,0.1106383,0.00005628745,0.000097987,0.000008245622,0.00002746175,0.00003283799,0.0000490493],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5065117,"threshold_uncertainty_score":0.5859131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02076080774955685,"score_gpt":0.2496749336075192,"score_spread":0.2289141258579624,"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."}}