{"id":"W4398765200","doi":"10.1109/wts60164.2024.10536688","title":"An Approach for Localizing User Terminals in 6G Mobile Networks","year":2024,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Context (archaeology); Trajectory; Terminal (telecommunication); Position (finance); Augmented reality; Terahertz radiation; Set (abstract data type); Artificial intelligence; Computer vision; Mobile robot; Robotics; Real-time computing; Telecommunications; Robot; Optics; Physics","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":[0.0001155512,0.0001014938,0.0001096313,0.0001368378,0.00002142239,0.00007989549,0.0001221508,0.0001330208,0.00003130676],"category_scores_gemma":[0.000005545781,0.00008845648,0.00003545861,0.0002603745,0.00001893814,0.0001588564,0.00001311794,0.0001064528,0.000005314478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003802167,"about_ca_system_score_gemma":0.00000557282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008107851,"about_ca_topic_score_gemma":0.000007871107,"domain_scores_codex":[0.9994218,0.000005721613,0.0001543439,0.0001547899,0.00004738289,0.000215978],"domain_scores_gemma":[0.99978,0.00002987675,0.000004111244,0.0001519382,0.00001118061,0.00002290088],"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":[0.000001991834,0.0000127194,0.0003128859,0.000140109,0.00000872628,0.000003905515,0.00009943685,0.9646592,0.0001837029,0.005845539,0.002004734,0.02672703],"study_design_scores_gemma":[0.00008088023,0.00002329244,0.00003286002,0.00002146288,0.000004548958,0.000002684278,0.000390992,0.9851753,0.004321139,0.0002032366,0.009613692,0.000129957],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00903858,0.0009437302,0.9845166,0.000006678557,0.000180696,0.0002852644,0.000003058076,0.001733529,0.003291898],"genre_scores_gemma":[0.9917356,0.0000549525,0.007579043,0.00003482747,0.00007143532,0.0002363083,0.00002686826,0.00003626254,0.0002246455],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9826971,"threshold_uncertainty_score":0.360715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008975096257018695,"score_gpt":0.2506582357365345,"score_spread":0.2416831394795158,"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."}}