{"id":"W2904473038","doi":"10.31701/itsnt2018.12","title":"Low-cost high-precision GNSS: challenges and opportunities","year":2018,"lang":"en","type":"preprint","venue":"","topic":"GNSS positioning and interference","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"GNSS applications; Computer science; Remote sensing; Global Positioning System; Telecommunications; Geology","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":[0.0001118833,0.0002449594,0.0002420371,0.0001093704,0.00003986138,0.00009805962,0.0001931017,0.0002639537,0.0002163879],"category_scores_gemma":[0.00001300591,0.000226789,0.00003926924,0.00001056347,0.00006892196,0.00008201825,0.00029196,0.0003187136,0.00009138224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003500785,"about_ca_system_score_gemma":0.00001533524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002268176,"about_ca_topic_score_gemma":0.00001535555,"domain_scores_codex":[0.9991914,0.00002131694,0.0002040521,0.000273708,0.0001236876,0.000185859],"domain_scores_gemma":[0.9993966,0.00004562745,0.00002961901,0.0003628368,0.00007330478,0.00009204526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003633745,0.0001172089,0.00001729683,0.002890632,0.0003785081,0.00003129439,0.005333979,0.004247838,0.0006363221,0.03271063,0.06736458,0.8862354],"study_design_scores_gemma":[0.003784329,0.001621134,0.03345354,0.03886441,0.0007230669,0.0003041232,0.007767679,0.3090451,0.1643873,0.239522,0.1870319,0.01349545],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4147945,0.01546856,0.01563513,0.0008729027,0.004860369,0.0005281618,0.0001153475,0.002101262,0.5456238],"genre_scores_gemma":[0.9672117,0.03041519,0.0008461027,0.00004314115,0.0002607798,0.00004585558,0.00005289468,0.00003856382,0.001085745],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8727399,"threshold_uncertainty_score":0.9248187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07541667748625233,"score_gpt":0.2523996642784212,"score_spread":0.1769829867921689,"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."}}