{"id":"W2947248637","doi":"10.1109/access.2019.2918987","title":"Triple-Frequency Combining Observation Models and Performance in Precise Point Positioning Using Real BDS Data","year":2019,"lang":"en","type":"article","venue":"IEEE Access","topic":"GNSS positioning and interference","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Precise Point Positioning; Point (geometry); Global Positioning System; Telecommunications; GNSS applications; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001561366,0.0006789057,0.0005351717,0.0006201474,0.0004673276,0.0007893438,0.0006879364,0.0007597665,0.0006026553],"category_scores_gemma":[0.003788166,0.0003300281,0.0008233892,0.000953723,0.0003923835,0.001261021,0.0008862945,0.0006899001,0.0002236649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006146277,"about_ca_system_score_gemma":0.0008798623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02829514,"about_ca_topic_score_gemma":0.01255455,"domain_scores_codex":[0.9992606,0.0001688982,0.00004273863,0.0002007582,0.0002336627,0.00009319835],"domain_scores_gemma":[0.9988539,0.0004456251,0.0001455751,0.0002121672,0.0002818338,0.00006080784],"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":[0.0004138915,0.00007855041,0.02883123,0.0001093444,0.000108033,0.0001356933,0.0002483255,0.8513851,0.007601791,0.003613927,0.0005682019,0.1069059],"study_design_scores_gemma":[0.000009234108,0.00006318461,0.003613511,0.000005074961,0.00002244039,0.00003437759,0.00003285968,0.9937663,0.001553516,0.0005926919,0.000285551,0.0000212647],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5960595,0.0004782641,0.3995342,0.0001923799,0.00006984994,0.00004470073,0.0002568642,0.0007513216,0.002612956],"genre_scores_gemma":[0.9618857,0.0001345826,0.03718589,0.00001624565,0.00001148944,0.00002038074,0.0003331792,0.00003207479,0.0003804316],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02829514,"threshold_uncertainty_score":0.05626088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1005947683139485,"score_gpt":0.3035266540193098,"score_spread":0.2029318857053613,"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."}}