{"id":"W1982725971","doi":"10.1109/pawr.2013.6490177","title":"Concurrent dual band digital predistortion using look up tables with variable depths","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Power Amplifier Design","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Alberta Innovates - Technology Futures","keywords":"Predistortion; Lookup table; Multi-band device; Linearization; Amplifier; Transmitter; Computer science; Nonlinear distortion; Electronic engineering; Distortion (music); Intermodulation; Compensation (psychology); Nonlinear system; Bandwidth (computing); Telecommunications; Engineering; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0000264105,0.0001606698,0.0001327075,0.00004077135,0.00004303053,0.0001288559,0.00005995473,0.00004803811,0.0005982707],"category_scores_gemma":[0.000009076616,0.0001357297,0.00001738998,0.0001101532,0.00003493965,0.0009521153,0.00001415069,0.00009144651,0.00008929083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001048421,"about_ca_system_score_gemma":0.00002458017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004815904,"about_ca_topic_score_gemma":0.000005967913,"domain_scores_codex":[0.9992515,0.000005146056,0.0001627525,0.0001655196,0.0001398097,0.0002752395],"domain_scores_gemma":[0.999633,0.00003288683,0.00002343614,0.0001615215,0.00005320123,0.00009601749],"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":[0.00002985704,0.000154637,0.01647863,0.0003608012,0.0003931467,0.00002017003,0.001024458,0.8467042,0.06353849,0.004654919,0.03972161,0.02691911],"study_design_scores_gemma":[0.004821185,0.0004781509,0.004033682,0.0004468724,0.0002186462,0.0003623124,0.001055632,0.8056602,0.08056754,0.002936804,0.09606961,0.003349394],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09015271,0.0001559235,0.8957069,0.000002161556,0.0004575735,0.0002653128,0.00001611812,0.0003562757,0.012887],"genre_scores_gemma":[0.9900935,0.00000374218,0.008410535,0.0000111761,0.00007795653,0.0000270444,0.0000279494,0.00004378787,0.001304368],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8999407,"threshold_uncertainty_score":0.6550645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01177608796943184,"score_gpt":0.2023122075609069,"score_spread":0.190536119591475,"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."}}