{"id":"W4386832077","doi":"10.3390/electronics12183928","title":"Predictive Modeling of Signal Degradation in Urban VANETs Using Artificial Neural Networks","year":2023,"lang":"en","type":"article","venue":"Electronics","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Computer science; Mean squared error; Multipath propagation; Artificial neural network; Transmission (telecommunications); Real-time computing; Fading; Network packet; Key (lock); Machine learning; Simulation; Data mining; Artificial intelligence; Algorithm; Telecommunications; Computer network; Statistics","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":[0.0007533385,0.0007299821,0.0004703041,0.0004537295,0.0002797385,0.0006579273,0.0007762042,0.0007502672,0.0004508243],"category_scores_gemma":[0.002424825,0.0003441105,0.000394425,0.0004380093,0.0004579718,0.0006369113,0.0004614897,0.0007784027,0.00009575298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008164012,"about_ca_system_score_gemma":0.0004168798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01292052,"about_ca_topic_score_gemma":0.006420232,"domain_scores_codex":[0.9997562,0.00006862558,0.00001857972,0.00005315531,0.00006189548,0.00004162122],"domain_scores_gemma":[0.998902,0.0006671769,0.0001444076,0.00003716801,0.0002263572,0.00002289523],"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":[0.000009474713,0.000005173363,0.000337947,0.000003807965,0.000003378838,0.000007476589,0.000004224853,0.9979746,0.0001168514,0.0001125887,0.0000208993,0.00140359],"study_design_scores_gemma":[2.985417e-7,0.000002767208,0.00005918019,5.317212e-7,5.354337e-7,9.246932e-7,9.046771e-7,0.9998119,0.00004722627,0.00006653935,0.000008528285,6.091726e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4484572,0.000630994,0.5455742,0.0003444453,0.00008973541,0.00007931086,0.0002137376,0.0006335935,0.003976774],"genre_scores_gemma":[0.990784,0.0001267731,0.00815189,0.00002652508,0.000009146738,0.00003466481,0.0000742598,0.00001067683,0.0007820666],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01292052,"threshold_uncertainty_score":0.02569067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01628222214764102,"score_gpt":0.2231866566727487,"score_spread":0.2069044345251077,"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."}}