{"id":"W4403391682","doi":"10.21203/rs.3.rs-5066621/v1","title":"Best Group Random User Selection and Beamforming","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Beamforming; Selection (genetic algorithm); Group selection; Group (periodic table); Computer science; User group; Artificial intelligence; World Wide Web; Telecommunications; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002891226,0.002190821,0.002037867,0.001656283,0.0009577328,0.001980277,0.001632659,0.001949359,0.00659113],"category_scores_gemma":[0.01373233,0.00114453,0.00123391,0.003744447,0.001515162,0.002699827,0.001818826,0.001355846,0.002738847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009855091,"about_ca_system_score_gemma":0.00125199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001774669,"about_ca_topic_score_gemma":0.003371537,"domain_scores_codex":[0.996076,0.002378525,0.00009454953,0.0004903853,0.0006901357,0.000270385],"domain_scores_gemma":[0.9949432,0.003750833,0.0002053785,0.0005968582,0.0003938763,0.0001097447],"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":[0.0007460025,0.0001432743,0.001282125,0.0002867466,0.0003789549,0.0002362904,0.0002384581,0.6305044,0.005602892,0.1508113,0.01941999,0.1903496],"study_design_scores_gemma":[0.00007353604,0.0000746314,0.0002954511,0.00003505591,0.00005537531,0.0002086546,0.00005714455,0.9067216,0.001942718,0.08782636,0.002678733,0.00003083267],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003989037,0.0005432006,0.991438,0.0004780583,0.0001231121,0.00004959011,0.0001080658,0.0002078588,0.003063171],"genre_scores_gemma":[0.3616878,0.002657197,0.6087549,0.0007210562,0.0009943024,0.0006499565,0.0006923896,0.0003569688,0.02348527],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00659113,"threshold_uncertainty_score":0.02204955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03741727789041003,"score_gpt":0.3459982520253523,"score_spread":0.3085809741349423,"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."}}