{"id":"W2611102272","doi":"10.1007/978-981-10-4591-2_21","title":"Ionospheric STEC and VTEC Constraints for Fast PPP","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in electrical engineering","topic":"GNSS positioning and interference","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Ionosphere; Convergence (economics); Initialization; Constraint (computer-aided design); VTEC; Position (finance); Computer science; Precise Point Positioning; Geodesy; Mathematics; Telecommunications; GNSS applications; Geography; Global Positioning System; Physics; Geophysics; Economics","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":[0.0000675496,0.0004460525,0.0004814427,0.0001603905,0.00006363053,0.00009478353,0.0002193367,0.000473905,0.00002910936],"category_scores_gemma":[0.0001997274,0.0004738482,0.0001031655,0.00003352348,0.00006294724,0.00006415872,0.0000291561,0.000896806,0.000009571173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001682782,"about_ca_system_score_gemma":0.00002555931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004431794,"about_ca_topic_score_gemma":0.000007926312,"domain_scores_codex":[0.9987988,0.000002933778,0.0002909231,0.0003463619,0.0001216629,0.0004392839],"domain_scores_gemma":[0.9992505,0.0002812301,0.00005176266,0.0002749928,0.00003896396,0.0001026012],"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":[0.00003135818,0.00002154984,0.00002444349,0.0008336,0.000296762,0.00004395226,0.0002381416,0.3122127,0.005372154,0.02092364,0.0002734882,0.6597282],"study_design_scores_gemma":[0.001184131,0.0003611041,0.0002613742,0.001843682,0.000138467,0.0001763107,6.984593e-7,0.9484831,0.005824216,0.01198237,0.02763796,0.0021066],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0005397458,0.005017544,0.9371262,0.00005851611,0.0007100298,0.00058595,0.00005174584,0.0005995352,0.05531075],"genre_scores_gemma":[0.9910759,0.0003625905,0.005857422,0.00003658343,0.0003534318,0.0000601074,0.00003724448,0.0001835056,0.002033254],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9905361,"threshold_uncertainty_score":0.9997713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00757059471562796,"score_gpt":0.1993583364392006,"score_spread":0.1917877417235727,"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."}}