{"id":"W6925376388","doi":"10.17632/3d3sb7y65z.1","title":"Evaluating Wireless Network Technologies (3G, 4G, 5G) and Their Infrastructure: A Systematic Review","year":2024,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Urban Development and Societal Issues","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wireless network; Key (lock); Personalization; Wireless; Emerging technologies; Wireless WAN","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.004366848,0.00067149,0.001412767,0.000117227,0.001237263,0.001079927,0.0034604,0.0003986465,0.00002532686],"category_scores_gemma":[0.0002383342,0.0004868569,0.00009899367,0.0007757635,0.0005674799,0.0005172438,0.003288165,0.0009380739,0.00004776724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000076148,"about_ca_system_score_gemma":0.0002452333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001516701,"about_ca_topic_score_gemma":0.00967772,"domain_scores_codex":[0.9956436,0.0008479979,0.0008229453,0.001116887,0.0007365269,0.0008320188],"domain_scores_gemma":[0.9967979,0.0009709412,0.0005300296,0.001464948,0.00007543024,0.0001607216],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005471671,0.00001024249,0.0001916944,0.1836384,0.000381476,0.00001113822,0.006548055,0.000006205948,0.000001797192,0.00004225391,0.8055041,0.003659136],"study_design_scores_gemma":[0.0001447905,0.000052823,0.0001381113,0.3055522,0.001718834,0.00001993286,0.01456105,0.006398458,4.13239e-7,0.003407413,0.6668319,0.001174109],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002287687,0.3423514,0.00002106155,0.0006343737,0.001070692,0.002410715,0.6499222,0.0007557902,0.0005461059],"genre_scores_gemma":[0.001563093,0.3132905,0.0005655888,0.0004579153,0.0008424164,0.0001559152,0.6827827,0.00005937817,0.0002825212],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1386723,"threshold_uncertainty_score":0.999957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03129767077427197,"score_gpt":0.3304610209680264,"score_spread":0.2991633501937544,"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."}}