{"id":"W7071074756","doi":"","title":"Robust, Multi-Constellation, Multi-Frequency Precise Point Positioning for Instantaneous cm-level Positioning","year":2025,"lang":"en","type":"other","venue":"York University Digital Library (York University)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Pseudorange; Precise Point Positioning; GNSS applications; Multipath propagation; BeiDou Navigation Satellite System; Global Positioning System; Satellite navigation; Outlier; Satellite; Geodetic datum","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00004000702,0.0005287045,0.00040533,0.0008028745,0.0004420614,0.0002448759,0.0008637595,0.0007263771,0.0002646681],"category_scores_gemma":[0.00004916541,0.0006987382,0.0003540853,0.0005643826,0.0002315401,0.0001451099,0.0005873085,0.0003432464,0.00004193837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001349107,"about_ca_system_score_gemma":0.000519574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005643746,"about_ca_topic_score_gemma":0.00004969466,"domain_scores_codex":[0.9983019,0.00008626132,0.0002685013,0.0007052409,0.000180507,0.0004576517],"domain_scores_gemma":[0.9986244,0.00006994254,0.0004372989,0.0005666921,0.00008680689,0.0002149028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002110245,0.00134509,0.01394862,0.001741364,0.003103011,0.0007998164,0.0005875322,0.01177605,0.0009115215,0.02282016,0.9320479,0.008808689],"study_design_scores_gemma":[0.003138137,0.0002824657,0.00009117222,0.0007389875,0.000243615,0.0000535794,0.00119316,0.001727503,0.0002848026,0.00003742924,0.9910111,0.001198018],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0003250691,0.0002948304,0.1366738,0.0001133275,0.000281852,0.0009937182,0.00659786,0.0004806446,0.8542389],"genre_scores_gemma":[0.005926715,0.0001936899,0.1021326,0.0001468035,0.000164957,3.711411e-7,0.009429236,0.0002218753,0.8817838],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05896324,"threshold_uncertainty_score":0.9995463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0164730012331558,"score_gpt":0.1919434660374648,"score_spread":0.1754704648043091,"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."}}