{"id":"W6976544882","doi":"10.60692/9xseg-96b02","title":"Intelligent Bi-directional Relaying Communication for Edge Intelligence based Industrial IoT Networks","year":2022,"lang":"en","type":"article","venue":"Greater South Information System","topic":"IoT Networks and Protocols","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Enhanced Data Rates for GSM Evolution; Rayleigh fading; Channel (broadcasting); Group (periodic table); Range (aeronautics); Order (exchange); Channel state information","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004235779,0.0003993183,0.0002245133,0.0005262641,0.0004222916,0.0008300095,0.0004402549,0.0003798183,0.001045168],"category_scores_gemma":[0.001041148,0.00008953545,0.0002194251,0.0004149363,0.0003422172,0.001050053,0.0004325092,0.000390023,0.0002654155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004292142,"about_ca_system_score_gemma":0.0002585095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006654822,"about_ca_topic_score_gemma":0.001131119,"domain_scores_codex":[0.9997836,0.00006648355,0.00001291224,0.00003806167,0.00006929624,0.00002977579],"domain_scores_gemma":[0.9995327,0.0002247756,0.00004936624,0.00007519352,0.0001007992,0.00001718795],"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":[0.0003489982,0.0001789552,0.004718495,0.0004425606,0.0001039944,0.0006997063,0.000839208,0.2811477,0.07421556,0.225868,0.005139128,0.4062977],"study_design_scores_gemma":[0.00001428436,0.0005225362,0.00211235,0.00004250612,0.00009506771,0.0007431246,0.0003160994,0.9050738,0.02076652,0.04826238,0.0220086,0.00004277214],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1544713,0.003438717,0.8090971,0.0007566369,0.0001576685,0.00007969284,0.00007895081,0.0002453256,0.03167462],"genre_scores_gemma":[0.9475017,0.002050643,0.04475059,0.00007450704,0.0000545503,0.00003063651,0.00007382077,0.00001603751,0.005447519],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001045168,"threshold_uncertainty_score":0.003496408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07220930167177496,"score_gpt":0.2345778539402589,"score_spread":0.1623685522684839,"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."}}