{"id":"W2149524429","doi":"10.2528/pierc10032801","title":"A BROADBAND DUAL-INFLECTION POINT RF PREDISTORTION LINEARIZER USING BACKWARD REFLECTION TOPOLOGY","year":2010,"lang":"en","type":"article","venue":"Progress In Electromagnetics Research C","topic":"Advanced Power Amplifier Design","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Linearizer; Predistortion; Broadband; Topology (electrical circuits); Inflection point; Dual (grammatical number); Reflection (computer programming); Point (geometry); Computer science; Engineering; Telecommunications; Electrical engineering; Mathematics; Bandwidth (computing); Amplifier; Geometry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00107683,0.0002274225,0.0002325411,0.0007157451,0.0001781837,0.0001075429,0.0002046597,0.0003263759,0.0001245783],"category_scores_gemma":[0.0002153388,0.0002573162,0.00004964682,0.00115736,0.0003248975,0.0002707221,0.00006853896,0.00198935,0.00002754983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004831436,"about_ca_system_score_gemma":0.0001130024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004361408,"about_ca_topic_score_gemma":0.0004107216,"domain_scores_codex":[0.9973323,0.0001780811,0.0004087279,0.0004359815,0.0005710092,0.001073909],"domain_scores_gemma":[0.9989322,0.0001369155,0.00004414373,0.0004305861,0.0002995702,0.000156533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001897623,0.0001633469,0.004656803,0.0001151706,0.00003199585,0.00004589696,0.0004263557,0.002657102,0.9600611,0.000817301,0.0007272831,0.03010794],"study_design_scores_gemma":[0.002691519,0.003486014,0.009241923,0.0001251576,0.00004431956,0.0006055922,0.0001144047,0.444222,0.4891589,0.02383665,0.02514109,0.001332409],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9666524,0.002097043,0.02245273,0.0002085389,0.001406125,0.001080915,0.000004641688,0.0005258141,0.005571785],"genre_scores_gemma":[0.979692,0.00020881,0.01918341,0.000008069128,0.0004035692,0.0001950204,0.00001461791,0.00008892029,0.000205594],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4709022,"threshold_uncertainty_score":0.9999879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04251687299527283,"score_gpt":0.3736903456259961,"score_spread":0.3311734726307232,"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."}}