{"id":"W2316508992","doi":"10.1515/jag-2014-0008","title":"Challenges in Assessing PPP Performance","year":2014,"lang":"en","type":"article","venue":"Journal of Applied Geodesy","topic":"GNSS positioning and interference","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Pseudorange; Precise Point Positioning; GNSS applications; Multipath propagation; Computer science; Global Positioning System; Ambiguity resolution; Satellite; Real-time computing; Geodesy; Telecommunications; Geography; Engineering","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":[0.0002889583,0.00007003977,0.000138766,0.0001050803,0.00001879583,0.00003179987,0.0001044468,0.00004093466,0.000007779721],"category_scores_gemma":[0.000007571738,0.00006329895,0.00002537556,0.00005380157,0.00001170196,0.0001451459,0.000007948931,0.0002410529,0.00001439212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003023336,"about_ca_system_score_gemma":0.000007894455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.078758e-7,"about_ca_topic_score_gemma":0.000002548263,"domain_scores_codex":[0.9994891,0.000006868181,0.0002228391,0.00004995697,0.0001042133,0.0001270812],"domain_scores_gemma":[0.9997746,0.00003245365,0.00005568519,0.00007417564,0.00002567036,0.00003736395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005633146,0.00009759975,0.00136402,0.0003209579,0.00005722134,0.000006905842,0.002276691,0.3293226,0.02616933,0.01022851,0.0006219344,0.6294779],"study_design_scores_gemma":[0.003699342,0.0006568772,0.3659128,0.002513188,0.00007038054,0.000440168,0.001774248,0.4844844,0.1012822,0.008224204,0.02970895,0.001233139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8491585,0.0002861059,0.001334023,0.00005200255,0.0001733028,0.00001605388,9.358599e-8,0.00002271707,0.1489572],"genre_scores_gemma":[0.9983153,0.0004146125,0.001109327,0.0000186699,0.0001243817,0.00000133208,2.514348e-7,0.00001033967,0.000005772941],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6282448,"threshold_uncertainty_score":0.2581257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02514748722866484,"score_gpt":0.2304570573830442,"score_spread":0.2053095701543793,"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."}}