{"id":"W2145868901","doi":"10.1023/b:bitn.0000014566.23457.85","title":"An Algorithm for Combined Code and Carrier Phase Based GPS Positioning","year":2003,"lang":"en","type":"article","venue":"BIT Numerical Mathematics","topic":"GNSS positioning and interference","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Global Positioning System; Algorithm; Position (finance); Computer science; Code (set theory); GPS signals; Time to first fix; GPS/INS; Assisted GPS; Reliability (semiconductor); Phase (matter); Kinematics; Telecommunications","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":[0.00008896025,0.0001289868,0.0001765052,0.00003802753,0.00009013312,0.00006779632,0.0000631845,0.00005629595,0.0000394879],"category_scores_gemma":[0.00004531322,0.0001256017,0.00003667031,0.00008140567,0.00002930238,0.00007777473,0.000003801417,0.00007917303,0.000007946903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002371551,"about_ca_system_score_gemma":0.00001056976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001052604,"about_ca_topic_score_gemma":1.412691e-7,"domain_scores_codex":[0.9993989,0.0000174391,0.0001899058,0.0001239767,0.0000843328,0.0001853715],"domain_scores_gemma":[0.9995496,0.0001077737,0.00002711218,0.0001523656,0.00004499696,0.0001181522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002672088,0.0153661,0.0007866803,0.006459107,0.001434537,0.0001021746,0.01917584,0.06742892,0.2772644,0.3475444,0.033567,0.2306035],"study_design_scores_gemma":[0.0009374095,0.0003512795,0.000009306503,0.0000594205,0.000032382,0.00001426868,0.00009079422,0.9816035,0.01346039,0.002599784,0.0006490076,0.0001924465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02816315,0.00005031096,0.9696111,0.0000215389,0.0000909836,0.0001678315,0.0001026146,0.0002074097,0.001585081],"genre_scores_gemma":[0.7755086,0.000002175509,0.2242806,0.00006158443,0.00001673178,0.0000472122,0.00003433808,0.00002486287,0.00002387798],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9141746,"threshold_uncertainty_score":0.5121889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01593071988128326,"score_gpt":0.2690526226503188,"score_spread":0.2531219027690356,"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."}}