{"id":"W2122731998","doi":"10.5194/isprsarchives-xl-2-173-2014","title":"Enhanced model for precise point positioning with single and dual frequency GPS/Galileo observables","year":2014,"lang":"en","type":"article","venue":"The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences","topic":"GNSS positioning and interference","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Global Positioning System; Galileo (satellite navigation); Precise Point Positioning; GNSS applications; Computer science; Satellite; UTC offset; Offset (computer science); Geodesy; Remote sensing; Real-time computing; Geography; Engineering; Telecommunications; Aerospace engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006725339,0.0009627609,0.0008099824,0.0004827078,0.0003195437,0.001056734,0.002040586,0.001150978,0.003382459],"category_scores_gemma":[0.001242334,0.0006635032,0.001062433,0.0007867545,0.0005199331,0.001435793,0.001366292,0.001508658,0.001540784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007955718,"about_ca_system_score_gemma":0.0009982741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01054077,"about_ca_topic_score_gemma":0.006630998,"domain_scores_codex":[0.999339,0.0001434452,0.00002737105,0.0002031141,0.0002255135,0.00006150216],"domain_scores_gemma":[0.9996394,0.000109253,0.0000649165,0.00004736927,0.0001228822,0.0000161835],"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":[0.00003303686,0.00002297375,0.001067409,0.00005969903,0.00004001572,0.00009336892,0.00004452333,0.9644917,0.00169141,0.01291962,0.001021147,0.01851493],"study_design_scores_gemma":[0.000006576987,0.00001537309,0.0002834105,0.000004829756,0.00001243866,0.00002586621,0.000003897884,0.9959993,0.0002380072,0.001981782,0.001419582,0.000008813201],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005784534,0.0001546821,0.9904689,0.000108765,0.00007009222,0.00002822709,0.0002145213,0.0002597996,0.002910462],"genre_scores_gemma":[0.7748648,0.001015869,0.1844118,0.000310195,0.0002855713,0.0005251709,0.001978531,0.0003631316,0.03624486],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01054077,"threshold_uncertainty_score":0.02095878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01682539265856039,"score_gpt":0.229156707316057,"score_spread":0.2123313146574966,"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."}}