{"id":"W2074536625","doi":"10.1007/s10291-011-0244-6","title":"Improving vertical GPS precision with a GPS-over-fiber architecture and real-time relative delay calibration","year":2011,"lang":"en","type":"article","venue":"GPS Solutions","topic":"GNSS positioning and interference","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure; Université Laval; Centre de Géomatique du Québec","funders":"Natural Sciences and Engineering Research Council of Canada; Instituto Tecnológico y de Estudios Superiores de Monterrey","keywords":"Global Positioning System; Calibration; Computer science; Precision Lightweight GPS Receiver; Baseline (sea); Component (thermodynamics); Assisted GPS; Antenna (radio); Real-time computing; Electronic engineering; Gps receiver; Engineering; Telecommunications; Mathematics; Physics; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0000648817,0.0001345667,0.0001120817,0.0000693295,0.0001799092,0.00003787371,0.00006303682,0.00009968523,0.0001490736],"category_scores_gemma":[0.00003173836,0.0001145054,0.00002868436,0.0001162465,0.00007805843,0.000278091,0.00003722016,0.0002188236,0.00005563483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005460492,"about_ca_system_score_gemma":0.00002291318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002610073,"about_ca_topic_score_gemma":0.00006124943,"domain_scores_codex":[0.9992787,0.00003544514,0.0001502997,0.0001889482,0.0001060796,0.000240526],"domain_scores_gemma":[0.99962,0.00006022033,0.00001806395,0.0001698792,0.00003698515,0.00009480612],"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":[0.001566163,0.001214912,0.007217169,0.0005591271,0.001576151,0.0001353799,0.08091846,0.1048389,0.5898879,0.1179283,0.02255715,0.07160036],"study_design_scores_gemma":[0.00168272,0.001248485,0.06393393,0.0007294947,0.0003500841,0.0003137836,0.0002395634,0.9098041,0.0111979,0.008576943,0.0006587654,0.001264227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5987774,0.0001386841,0.3546558,0.00006277817,0.0001095685,0.0002527846,0.00003335649,0.0005041223,0.0454656],"genre_scores_gemma":[0.9895836,0.00001129202,0.0098426,0.00001097722,0.0000379618,0.00002583927,0.00001926722,0.00002391367,0.0004445427],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8049652,"threshold_uncertainty_score":0.4669393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01353675362651432,"score_gpt":0.2013149658677455,"score_spread":0.1877782122412311,"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."}}