{"id":"W7119099652","doi":"10.5281/zenodo.18168532","title":"IoT and Massive Connectivity: Massive MIMO Optimization for IoT Connectivity in 5G and Beyond Networks","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Marriott International (Canada)","funders":"","keywords":"MIMO; Orchestration; Internet of Things; Efficient energy use; Key (lock); Wireless; Focus (optics); Channel (broadcasting); Energy consumption","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":[0.0004028762,0.0006906491,0.0004628117,0.0001805263,0.0002334579,0.0007197891,0.0003391962,0.0005094004,0.001822935],"category_scores_gemma":[0.001317588,0.0001935115,0.0003143855,0.0004332127,0.0005791423,0.0006355997,0.0005839151,0.0007518926,0.0002432728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004895248,"about_ca_system_score_gemma":0.0004763912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001567475,"about_ca_topic_score_gemma":0.001749223,"domain_scores_codex":[0.9998214,0.00007046263,0.000004466752,0.00002501282,0.00004941079,0.00002926649],"domain_scores_gemma":[0.9996102,0.0002482028,0.00004344591,0.00002044067,0.00005609412,0.00002148031],"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":[0.0000491589,0.00003032927,0.0004144566,0.0000872012,0.00002833982,0.00009259036,0.00003888855,0.9414323,0.003040683,0.02917772,0.002741438,0.02286679],"study_design_scores_gemma":[0.000005221137,0.00003675248,0.0001711285,0.00001183118,0.000006890778,0.00002370722,0.00001682833,0.9848964,0.0004076973,0.01329995,0.001116695,0.000006823461],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02249453,0.002361996,0.9590205,0.001234846,0.0002080204,0.00003543719,0.0001019018,0.0001385412,0.01440424],"genre_scores_gemma":[0.9063711,0.003080038,0.08387351,0.0005368487,0.0004067915,0.00009067279,0.0001189196,0.00006059576,0.005461653],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001822935,"threshold_uncertainty_score":0.00609839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01871347615820244,"score_gpt":0.2348617469441865,"score_spread":0.216148270785984,"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."}}