{"id":"W4300698956","doi":"10.48550/arxiv.1709.05161","title":"Device Activity and Embedded Information Bit Detection Using AMP in\\n Massive MIMO","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"IoT Networks and Protocols","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Engineering Link (Canada)","funders":"","keywords":"Computer science; Network packet; Computer network; Distributed computing; Cellular network; Random access; MIMO; The Internet","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000130663,0.0002118022,0.0002223413,0.000223789,0.0001297645,0.0001257865,0.0001917939,0.0003608908,0.00001057066],"category_scores_gemma":[0.00001713381,0.000269675,0.00005793029,0.0001341327,0.0000399075,0.0007389272,0.0002401763,0.0005453844,0.00001751905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002486738,"about_ca_system_score_gemma":0.00003861877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003495682,"about_ca_topic_score_gemma":0.0005257039,"domain_scores_codex":[0.9993638,0.0000411824,0.0001227525,0.000223266,0.00004051588,0.0002085252],"domain_scores_gemma":[0.9993223,0.00003180754,0.0001532831,0.0003708031,0.00005569601,0.00006610443],"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":[0.00005296959,0.000007539768,0.001346005,0.0003118989,0.00004064514,0.00001734674,0.0002012852,0.9934631,0.0003202585,0.0001272005,0.00001351471,0.004098216],"study_design_scores_gemma":[0.0004404526,0.00001033377,0.0048531,0.0002132349,0.0000407034,0.00000238346,0.00003412205,0.99097,0.0006801587,0.001650132,0.0007687795,0.0003365855],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8955321,0.00001632245,0.1008177,0.000003229707,0.0003238119,0.001589478,0.000009630078,0.000105226,0.001602458],"genre_scores_gemma":[0.9995915,0.0000829149,0.0001629318,0.000006747405,0.00007205366,0.00001299042,0.000008990062,0.00001585179,0.00004602612],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1040593,"threshold_uncertainty_score":0.9999756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07231493538657542,"score_gpt":0.2084270269668302,"score_spread":0.1361120915802548,"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."}}