{"id":"W4313598753","doi":"10.1109/ojcoms.2023.3234193","title":"Analysis of a HAPS-Aided GNSS in Urban Areas Using a RAIM Algorithm","year":2023,"lang":"en","type":"article","venue":"IEEE Open Journal of the Communications Society","topic":"GNSS positioning and interference","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Huawei Technologies","keywords":"GNSS applications; Receiver autonomous integrity monitoring; Computer science; GNSS augmentation; Remote sensing; Algorithm; Environmental science; Geography; Global Positioning System; Telecommunications","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":[0.000682028,0.00007270096,0.0002588117,0.0001309105,0.0001339359,0.00006395635,0.001983689,0.00004486798,0.0000100235],"category_scores_gemma":[0.00003376762,0.00005918285,0.0003203527,0.001731848,0.00008679291,0.0001976151,0.0002769995,0.000332496,0.000002134075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001219556,"about_ca_system_score_gemma":0.00005665767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001389505,"about_ca_topic_score_gemma":0.00004689724,"domain_scores_codex":[0.9991517,0.0001270868,0.0004282055,0.00004975413,0.0001326056,0.0001106417],"domain_scores_gemma":[0.9986923,0.0001424064,0.0001970636,0.0007897648,0.0001462934,0.00003217176],"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":[0.00001436109,0.0003283034,0.02278437,0.00005041705,0.00524431,0.000002189775,0.03261672,0.8824968,0.0258488,0.00034007,0.02403303,0.006240621],"study_design_scores_gemma":[0.000297899,0.00001459904,0.01605197,0.0002747849,0.0003558652,0.000009937799,0.001357426,0.9797383,0.001254097,0.0002183446,0.0003354352,0.00009134928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9843222,0.000801534,0.0107049,0.001065587,0.0003517795,0.0002196236,0.00004693828,0.00003759069,0.002449816],"genre_scores_gemma":[0.9891239,0.0003576575,0.01037276,0.00003249615,0.00001335598,0.000004058852,0.000003991949,0.00001072927,0.00008105519],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09724149,"threshold_uncertainty_score":0.3686221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07742093834449713,"score_gpt":0.3314753845106456,"score_spread":0.2540544461661484,"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."}}