{"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 œinternational 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008811639,0.0003805524,0.0003700178,0.0005522968,0.001074026,0.0007784187,0.0008451586,0.00008057504,0.000002754477],"category_scores_gemma":[0.0004255035,0.0002453964,0.0002074588,0.0004712695,0.001906773,0.0006029223,0.0003588113,0.0003139456,0.000001059526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000432129,"about_ca_system_score_gemma":0.0001061893,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3374266,"about_ca_topic_score_gemma":0.1015144,"domain_scores_codex":[0.9970024,0.0001380121,0.001035848,0.0003363728,0.001036856,0.000450544],"domain_scores_gemma":[0.9975942,0.0008278881,0.0008033598,0.0003414633,0.0002966715,0.0001363944],"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":[0.0001181278,0.0000155059,0.00007105652,0.00006641271,0.00007695999,7.240735e-8,0.003947441,0.03847119,0.0116407,0.00003082364,0.00002666834,0.9455351],"study_design_scores_gemma":[0.0006925049,0.0002311865,0.000909346,0.0005681264,0.00004622167,0.0000951648,0.0009454952,0.9635131,0.02303304,0.009311724,0.0003531782,0.0003009686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03475202,0.00002668606,0.9529193,0.001492168,0.0008225827,0.00054013,0.00009989723,0.00007135641,0.009275848],"genre_scores_gemma":[0.9873242,0.00008994331,0.01187556,0.0004916905,0.0001023425,0.000001007503,0.00004341371,0.00001502438,0.00005680011],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9525722,"threshold_uncertainty_score":0.9999998,"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."}}