{"id":"W4396788636","doi":"10.48550/arxiv.2405.01692","title":"Multi-Layer Network Formation through HAPS Base Station and Transmissive RIS-Equipped UAV","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Global Affairs Canada","keywords":"Layer (electronics); Base station; Base (topology); Computer science; Environmental science; Computer network; Materials science; Nanotechnology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008697747,0.0002522841,0.0002010184,0.000109688,0.000115015,0.00008727859,0.0001432761,0.0002588561,0.00004889262],"category_scores_gemma":[0.000004496835,0.0003003138,0.00007983322,0.0003513651,0.00003827003,0.0003031931,0.0001243575,0.0003905257,0.00005637752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001586638,"about_ca_system_score_gemma":0.00003054037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006315334,"about_ca_topic_score_gemma":0.00008421095,"domain_scores_codex":[0.9990881,0.00003282008,0.0002016856,0.0004105365,0.00004926552,0.0002175883],"domain_scores_gemma":[0.9994304,0.00003507543,0.00007278714,0.0003033052,0.00008064094,0.00007778268],"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":[0.00001202313,0.00001384013,0.00006044226,0.0003140763,0.00006866032,0.00001348677,0.0005820196,0.9913545,0.0001172515,0.005934538,0.0009478745,0.0005812575],"study_design_scores_gemma":[0.0003652101,0.00001157578,0.0002918468,0.0001191205,0.0001831981,0.000001846974,0.0001186384,0.9859684,0.0001473753,0.0115638,0.0009221262,0.0003068808],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1473415,0.0004758424,0.8494203,0.00004631618,0.0002471308,0.0004827566,0.00008549829,0.0004133833,0.001487285],"genre_scores_gemma":[0.9851755,0.001852766,0.0121015,0.00002589465,0.0000900786,0.000007405251,0.0003331327,0.00004765909,0.0003660772],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.837834,"threshold_uncertainty_score":0.9999449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06032762242624768,"score_gpt":0.1861369478574788,"score_spread":0.1258093254312311,"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."}}