{"id":"W3216205907","doi":"10.1109/mcom.111.2001118","title":"Robotic Communications for 5G and Beyond: Challenges and Research Opportunities","year":2021,"lang":"en","type":"article","venue":"IEEE Communications Magazine","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Robotics; Robot; Context (archaeology); Mobile robot; Communications system; Trajectory; Artificial intelligence; Distributed computing; Telecommunications; Human–computer interaction","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004276905,0.0001139055,0.0001597404,0.0001528022,0.0004940592,0.00008707418,0.0005400309,0.00007952928,0.000008496503],"category_scores_gemma":[0.00007000902,0.0001329818,0.00002459293,0.000222852,0.0003834297,0.0001737561,0.0002100572,0.0002388811,0.00001201003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003668897,"about_ca_system_score_gemma":0.00004344002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004112031,"about_ca_topic_score_gemma":0.0002446884,"domain_scores_codex":[0.9991709,0.0001278683,0.0002419873,0.0001642869,0.00009957034,0.0001953895],"domain_scores_gemma":[0.9963809,0.000717371,0.00002908378,0.002354023,0.0004278611,0.00009080215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009253306,0.0004576595,0.00007809969,0.0005690136,0.0002097979,0.000001793142,0.004588057,0.005171114,0.007344023,0.6633641,0.01860838,0.2995988],"study_design_scores_gemma":[0.0007608376,0.0000665616,0.002100913,0.00009911179,0.00008597791,0.00005552578,0.002955491,0.3904312,0.0006938615,0.01908641,0.5831941,0.000469958],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.00614601,0.5071002,0.04751894,0.1192741,0.0004166758,0.002634411,0.0002106629,0.001178034,0.3155209],"genre_scores_gemma":[0.5016614,0.4038156,0.09213689,0.0001047915,0.00005040754,0.0007988288,0.0003186393,0.00005592618,0.001057588],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.6442776,"threshold_uncertainty_score":0.542284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2340880713712784,"score_gpt":0.3554827697597679,"score_spread":0.1213946983884895,"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."}}