{"id":"W2808747593","doi":"10.3390/s18061967","title":"GNSS Code Multipath Mitigation by Cascading Measurement Monitoring Techniques","year":2018,"lang":"en","type":"article","venue":"Sensors","topic":"GNSS positioning and interference","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Alberta Innovates","keywords":"GNSS applications; Multipath mitigation; Multipath propagation; Code (set theory); Computer science; Remote sensing; Real-time computing; Global Positioning System; Telecommunications; Geography; Programming language","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001220845,0.0001013663,0.00007803841,0.00004537152,0.00008405438,0.00003325775,0.00006781737,0.00005599829,0.000008062594],"category_scores_gemma":[0.00002844589,0.0001066415,0.00002436215,0.00006669352,0.00003217457,0.00007108424,0.000008816721,0.00009816967,0.00006137585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001372078,"about_ca_system_score_gemma":0.000003899054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003986298,"about_ca_topic_score_gemma":0.000005649809,"domain_scores_codex":[0.9993879,0.00001637434,0.0001279157,0.0001202415,0.0001709962,0.00017659],"domain_scores_gemma":[0.9996986,0.000009845797,0.000018356,0.0001201156,0.0001052403,0.00004785086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000004384984,0.0000150919,0.001484741,0.00003376507,0.00003182912,0.000001657275,0.001377811,0.0005832554,0.9822428,0.00004437862,0.004777847,0.00940249],"study_design_scores_gemma":[0.00005821595,0.00004049561,0.0005790719,0.0002103146,0.000006654386,0.000004252092,0.0001049379,0.01382069,0.9822638,0.00002740685,0.002749569,0.000134557],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9851482,0.0001195353,0.003409253,0.00002369026,0.0005013047,0.00008335429,0.00000803852,0.000704166,0.01000246],"genre_scores_gemma":[0.9975567,0.00002085227,0.002008483,0.000008330277,0.0002500729,0.0000122092,0.000002849142,0.00002335358,0.0001171363],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01323744,"threshold_uncertainty_score":0.4348715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02032084508895616,"score_gpt":0.2402382699376835,"score_spread":0.2199174248487273,"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."}}