{"id":"W4380046822","doi":"10.1109/plans53410.2023.10140012","title":"Super-Resolution GPS Receiver: User's Acceleration Computation","year":2023,"lang":"en","type":"article","venue":"","topic":"GNSS positioning and interference","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"GNSS applications; Baseband; Computer science; Global Positioning System; Doppler effect; Real-time computing; Pseudorange; Telecommunications; Physics","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":[0.0002780689,0.0004137255,0.0003889155,0.00037305,0.0001673927,0.0003956176,0.0006026361,0.0004394607,0.002351982],"category_scores_gemma":[0.001029487,0.0002252526,0.0003218162,0.000568622,0.0001657054,0.0006700331,0.0005148339,0.000572534,0.001472365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002972457,"about_ca_system_score_gemma":0.0005034548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002486329,"about_ca_topic_score_gemma":0.0026867,"domain_scores_codex":[0.9997081,0.0000343706,0.00001008281,0.00005263059,0.0001733861,0.0000212978],"domain_scores_gemma":[0.9998111,0.00003673303,0.00002036494,0.00003894061,0.00008218151,0.00001065918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002371119,0.0000596176,0.004146366,0.0001286323,0.00005417678,0.0001842175,0.0001962933,0.2302862,0.1034284,0.02404324,0.005598454,0.6316373],"study_design_scores_gemma":[0.000008239686,0.00004078456,0.0009872464,0.000007003456,0.00000885824,0.0001583427,0.00001370549,0.9791831,0.01191016,0.002054992,0.005613009,0.00001445626],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007923225,0.00009481245,0.9895466,0.00004500278,0.00002917644,0.00001393539,0.00004123588,0.000835781,0.001470309],"genre_scores_gemma":[0.2854886,0.0002503579,0.7090343,0.00009874926,0.00006813774,0.00005067432,0.0002703302,0.0001303304,0.004608483],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002486329,"threshold_uncertainty_score":0.007868111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02381185581079895,"score_gpt":0.2405261994677758,"score_spread":0.2167143436569768,"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."}}