{"id":"W4396853617","doi":"10.1109/fnwf58287.2023.10520460","title":"Wireless Quality of Service Modeling: Using Crowdsourced Data and Local Environment Features","year":2023,"lang":"en","type":"article","venue":"","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation, Science and Economic Development Canada","funders":"","keywords":"Computer science; Artificial neural network; Wireless network; Wireless; Service (business); Crowdsourcing; Quality of service; Wi-Fi; Mean squared error; Data modeling; Quality (philosophy); Real-time computing; Telecommunications; Artificial intelligence; World Wide Web; Database; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002835106,0.00009487483,0.0001412965,0.00005545069,0.00003482818,0.00001443093,0.0001353374,0.00005372734,0.00002679574],"category_scores_gemma":[0.00000560528,0.00009066275,0.00001496611,0.0000953669,0.00001517129,0.00008566332,0.0001875201,0.00007505633,0.000008087532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001647108,"about_ca_system_score_gemma":0.000005780571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000203097,"about_ca_topic_score_gemma":0.00003925137,"domain_scores_codex":[0.9992915,0.00002140874,0.0002303052,0.0001782708,0.0001441068,0.0001343885],"domain_scores_gemma":[0.9995365,0.00002402017,0.0000198997,0.0003521668,0.00001500467,0.00005243332],"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":[0.000004112696,0.000004349177,0.00002891716,0.0001229558,0.00001872284,3.695527e-7,0.0002477462,0.8624035,0.1343349,0.00002574744,0.00003067429,0.002778035],"study_design_scores_gemma":[0.0001578951,0.000002872222,0.000057189,0.00001512783,0.00001001179,0.000001301937,0.0004141952,0.9814458,0.01768926,0.00007399553,0.00002470237,0.0001076903],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5002338,0.00006772028,0.4993976,0.00003296798,0.00002019083,0.00004174063,0.00001505734,0.0000869721,0.0001038994],"genre_scores_gemma":[0.9959642,0.00008994318,0.003746845,0.00006545833,0.0000181624,0.000001368422,0.00006218722,0.00002040161,0.00003140481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4957304,"threshold_uncertainty_score":0.3697119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.132218761732353,"score_gpt":0.2984191344482253,"score_spread":0.1662003727158723,"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."}}