{"id":"W2276090935","doi":"10.1049/iet-com.2015.0371","title":"Complexity‐aware‐normalised mean squared error ‘CAN’ metric for dimension estimation of memory polynomial‐based power amplifiers behavioural models","year":2015,"lang":"en","type":"article","venue":"IET Communications","topic":"Advanced Power Amplifier Design","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"King Fahd University of Petroleum and Minerals","keywords":"Mean squared error; Metric (unit); Dimension (graph theory); Polynomial; Computer science; Estimation; Power (physics); Amplifier; Mathematics; Algorithm; Statistics; Telecommunications; Bandwidth (computing); Combinatorics","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":[0.001732741,0.001180215,0.0006822889,0.001025422,0.0003482309,0.001017233,0.0009383123,0.0008872446,0.001379842],"category_scores_gemma":[0.008325461,0.0002881182,0.0007153691,0.0007054271,0.0006054851,0.001181415,0.0008742565,0.000938572,0.0003237253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007657869,"about_ca_system_score_gemma":0.0008103491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003383545,"about_ca_topic_score_gemma":0.00347728,"domain_scores_codex":[0.9988101,0.0004138925,0.0001020882,0.0001667503,0.0004282201,0.00007912653],"domain_scores_gemma":[0.9956415,0.002860323,0.0003336515,0.0005108714,0.000580602,0.00007307757],"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":[0.0002833114,0.0000617513,0.002017876,0.0002127998,0.0001251021,0.00007616386,0.00009200705,0.875149,0.0123802,0.01098254,0.001088213,0.09753117],"study_design_scores_gemma":[0.000002480344,0.00003491742,0.0004862938,0.000009319062,0.00001045649,0.00003958115,0.00000990911,0.9944202,0.002810297,0.001734896,0.0004316142,0.00001000045],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03614601,0.0004531552,0.9608895,0.0001029939,0.00003792359,0.00002904797,0.000109624,0.0004445561,0.001787258],"genre_scores_gemma":[0.8469694,0.0004263651,0.1498876,0.00006694419,0.00004464857,0.0001196201,0.0004372184,0.0001563229,0.001892006],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003383545,"threshold_uncertainty_score":0.009163678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.161543274534785,"score_gpt":0.322104434085712,"score_spread":0.160561159550927,"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."}}