{"id":"W4388807706","doi":"10.17794/rgn.2023.4.9","title":"THE PERFORMANCE ANALYSIS OF THE POST-MISSION WEB-BASED STATIC AND KINEMATIC PPP-AR SERVICE","year":2023,"lang":"en","type":"article","venue":"Rudarsko-geološko-naftni zbornik","topic":"GNSS positioning and interference","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Resources Canada","keywords":"Precise Point Positioning; GNSS applications; Float (project management); Global Positioning System; GLONASS; Computer science; Real Time Kinematic; Geodesy; Kinematics; Real-time computing; Satellite; Service (business); Satellite system; Remote sensing; Geography; Telecommunications; Engineering; Systems engineering; Aerospace engineering; Business; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003947336,0.0002366965,0.0003269019,0.0002367158,0.0003279084,0.00007383944,0.000442541,0.0000916849,0.00006206883],"category_scores_gemma":[0.0001183999,0.0001488867,0.0001323758,0.001933306,0.0001140519,0.0001131584,0.0001024628,0.0002634283,0.00008976694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004322483,"about_ca_system_score_gemma":0.00006095086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007621775,"about_ca_topic_score_gemma":0.0001078952,"domain_scores_codex":[0.9985045,0.00009809907,0.000432208,0.000230703,0.0003519128,0.0003825984],"domain_scores_gemma":[0.9985793,0.0004193751,0.0001166532,0.0006133826,0.0001829913,0.00008831967],"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":[0.00009333865,0.00009628642,0.04485423,0.001887676,0.001445323,0.000007512948,0.002965766,0.8896594,0.0477715,0.0006998457,0.005680238,0.004838867],"study_design_scores_gemma":[0.0002611266,0.00005869273,0.1552757,0.0002465364,0.0003700262,0.000002530263,0.0001826282,0.8396199,0.002930039,0.00004935992,0.0008277557,0.0001756905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964938,0.0002430974,0.0001630731,0.001321475,0.0002426975,0.0002049622,0.00005998938,0.0002790036,0.0009919379],"genre_scores_gemma":[0.9990597,0.00016048,0.0001415019,0.0002449878,0.00002285708,0.00002519132,0.00005016695,0.00003147743,0.0002636099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1104215,"threshold_uncertainty_score":0.6071425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007252785184800921,"score_gpt":0.2095761007659168,"score_spread":0.2023233155811159,"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."}}