{"id":"W3090924458","doi":"10.1007/s10291-020-01034-6","title":"Understanding long-term variations in GPS differential code biases","year":2020,"lang":"en","type":"article","venue":"GPS Solutions","topic":"GNSS positioning and interference","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Satellite; Geodetic datum; Geodesy; Global Positioning System; Block (permutation group theory); Computer science; Mathematics; Geology; Physics; Telecommunications; Geometry","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":[0.00002466245,0.00009720129,0.0001024526,0.00007844484,0.0001456656,0.0000565995,0.00009915636,0.00005360345,0.000190069],"category_scores_gemma":[0.00004993284,0.0001107344,0.00004331048,0.0002205688,0.00003117534,0.0001206205,0.00003076193,0.0001736573,0.00009083736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001539091,"about_ca_system_score_gemma":0.0000181098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002001361,"about_ca_topic_score_gemma":0.0001877518,"domain_scores_codex":[0.9993668,0.00002086446,0.000166622,0.0001298062,0.00008020412,0.0002357435],"domain_scores_gemma":[0.9997309,0.00005733132,0.00001523256,0.0001002911,0.00001353326,0.00008266447],"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":[0.00005457754,0.0006622254,0.06983278,0.0003717609,0.0004625251,0.00006716152,0.01406757,0.4589759,0.05323538,0.3572763,0.04383194,0.001161951],"study_design_scores_gemma":[0.001027818,0.0001068191,0.1454027,0.0003775933,0.00008613155,0.0000166219,0.0003354945,0.8483988,0.001226573,0.002217454,0.0001920486,0.0006119456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1429814,0.0001086288,0.8481767,0.0007727471,0.0003974468,0.0001117871,0.0001008427,0.0004685752,0.006881857],"genre_scores_gemma":[0.9995188,0.000031145,0.0001732112,0.00004745101,0.00009734317,0.0000180421,0.00006369204,0.00001560715,0.00003469927],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8565374,"threshold_uncertainty_score":0.4515617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.18641858772742,"score_gpt":0.2716227144459347,"score_spread":0.08520412671851477,"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."}}