{"id":"W1591567090","doi":"","title":"Use of a Multi-Reference GPS Station Network for Precise 3D Positioning in Constricted Waterways","year":2000,"lang":"en","type":"article","venue":"The International Hydrographic Review","topic":"GNSS positioning and interference","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Global Positioning System; Reliability (semiconductor); Real Time Kinematic; Channel (broadcasting); Computer science; Environmental science; Marine engineering; Transport engineering; Engineering; GNSS applications; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002387495,0.0001186754,0.0001908845,0.0000797197,0.00004198836,0.00003916392,0.0002428085,0.0000377128,0.0001729358],"category_scores_gemma":[0.00003659036,0.0000919109,0.00008215458,0.000287185,0.00005127301,0.0001891145,0.00001181877,0.0001287438,0.00001401145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002907733,"about_ca_system_score_gemma":0.000009974644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001033341,"about_ca_topic_score_gemma":0.00005120054,"domain_scores_codex":[0.9990706,0.00004798438,0.0004420975,0.0001286201,0.0001531051,0.0001575535],"domain_scores_gemma":[0.9994613,0.0001779063,0.00007034168,0.0001537083,0.000111168,0.00002557613],"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":[0.0002076252,0.0004403764,0.005670275,0.002370707,0.0006599647,0.000006202954,0.0009430416,0.5298771,0.003163433,0.008583471,0.01230272,0.4357751],"study_design_scores_gemma":[0.001243753,0.0001996037,0.009915579,0.02237167,0.0001939787,0.000055872,0.00001676734,0.9024686,0.001326454,0.001708459,0.05988818,0.0006111171],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9024966,0.05141452,0.03010943,0.001017614,0.0009193232,0.003463328,0.0004818457,0.0004892171,0.009608172],"genre_scores_gemma":[0.9607707,0.03393669,0.00455687,0.0001579781,0.00003495815,0.0001957764,0.0002223615,0.0000158082,0.0001088976],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.435164,"threshold_uncertainty_score":0.3748018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04664235829879921,"score_gpt":0.2700521747690456,"score_spread":0.2234098164702464,"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."}}