{"id":"W2528875798","doi":"10.31298/sl.140.7-8.4","title":"Accuracy assessment of GPS precise point positioning (PPP) technique using different web-based online services in a forest environment","year":2016,"lang":"en","type":"article","venue":"Šumarski list","topic":"GNSS positioning and interference","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Resources Canada; Jet Propulsion Laboratory; National Aeronautics and Space Administration","keywords":"Global Positioning System; Computer science; Precise Point Positioning; Software; Process (computing); Remote sensing; Geography; Telecommunications; GNSS applications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0001192839,0.0002151728,0.0002534704,0.0001713455,0.00004568814,0.00003499475,0.0002011435,0.00008888193,0.0001231367],"category_scores_gemma":[0.00001037177,0.0001700167,0.00007305612,0.00008659204,0.00004800276,0.0001960103,0.00006304139,0.0001518387,0.000003909607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003831773,"about_ca_system_score_gemma":0.00002747458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000133323,"about_ca_topic_score_gemma":0.0002007574,"domain_scores_codex":[0.9988428,0.00004937808,0.0004259663,0.000227234,0.0001983661,0.0002562602],"domain_scores_gemma":[0.9993623,0.0001202108,0.0001064099,0.0003169457,0.00002683708,0.00006728699],"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":[0.00003933005,0.0006128931,0.06513721,0.0004403247,0.00004874804,0.00001386639,0.0001740374,0.04536144,0.8840375,0.00055041,0.00004209788,0.003542165],"study_design_scores_gemma":[0.002374379,0.0003550409,0.232499,0.006857132,0.00006690751,0.00002663741,0.0000946533,0.5699222,0.1859402,0.0007898727,0.0003104416,0.0007635221],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9364383,0.0000817272,0.06209906,0.0000886991,0.00008903633,0.0002996068,0.00009950048,0.0001141665,0.0006899406],"genre_scores_gemma":[0.9911262,0.00004562342,0.008587327,0.00002132691,0.00003561283,0.00007917769,0.00005259404,0.00003489952,0.00001720347],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6980972,"threshold_uncertainty_score":0.6933081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01148957780510179,"score_gpt":0.2539469760393933,"score_spread":0.2424573982342915,"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."}}