{"id":"W4286436784","doi":"10.18280/isi.270315","title":"A Stacked Autoencoder and Multilayer Perceptrons for mmWave Beamforming Prediction","year":2022,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Beamforming; Autoencoder; Computer science; Benchmark (surveying); Multilayer perceptron; Electronic engineering; Perceptron; Artificial neural network; Artificial intelligence; Computer engineering; Engineering; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003037617,0.0001329393,0.0001275847,0.0002109243,0.0004764481,0.00009549374,0.00006519091,0.00004770925,0.00007377346],"category_scores_gemma":[0.00004423622,0.0001465937,0.00004823477,0.0001212551,0.00002733344,0.00125371,0.00004905202,0.0001314528,0.000006435016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002947846,"about_ca_system_score_gemma":0.00002352462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000109795,"about_ca_topic_score_gemma":0.00000331983,"domain_scores_codex":[0.9990978,0.00001866571,0.0003976097,0.00009025862,0.0001708992,0.0002247411],"domain_scores_gemma":[0.9996455,0.00003074456,0.000071234,0.0001097363,0.00008345867,0.00005926795],"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":[0.00007114776,0.00002178077,0.0003792608,0.0008125951,0.00009920992,5.198289e-7,0.04250005,0.7939112,0.009915772,0.000490762,0.001421759,0.150376],"study_design_scores_gemma":[0.0004968761,0.00007784846,0.0003032893,0.00002166967,0.00001892887,0.00002441427,0.003358554,0.9858359,0.001461688,0.0005665658,0.007671706,0.0001625602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2621124,0.00007291244,0.7353294,0.00001474905,0.0003048674,0.0004737812,0.0001464524,0.0003200468,0.001225356],"genre_scores_gemma":[0.9848787,0.00002126695,0.01420419,0.00009480996,0.0000449763,0.0004137823,0.0002704569,0.00002149797,0.00005035007],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7227662,"threshold_uncertainty_score":0.5977918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01735707930152057,"score_gpt":0.2144175634223871,"score_spread":0.1970604841208665,"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."}}