{"id":"W1989404742","doi":"10.1109/tap.2013.2254695","title":"Space Mapping Optimization of Handset Antennas Exploiting Thin-Wire Models","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Antennas and Propagation","topic":"Microwave Engineering and Waveguides","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; McMaster University","keywords":"Space mapping; Handset; Computer science; Planar; Antenna (radio); Space (punctuation); Acoustics; Physics; Algorithm; Telecommunications; Computer graphics (images)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001892042,0.000636529,0.0004983147,0.000270208,0.0001807973,0.0005829828,0.0004446534,0.0004707398,0.00278047],"category_scores_gemma":[0.0005014215,0.000301967,0.0004938573,0.000264013,0.0003032164,0.0004529581,0.0006132284,0.0004135459,0.0006679281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003158603,"about_ca_system_score_gemma":0.000332448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007041059,"about_ca_topic_score_gemma":0.0007330799,"domain_scores_codex":[0.9998854,0.0000300511,0.000003547853,0.00001230114,0.00005013203,0.00001849228],"domain_scores_gemma":[0.9998201,0.00008071731,0.00002430786,0.00003418533,0.0000285405,0.00001230827],"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":[0.0000369509,0.0000230146,0.0002423536,0.00004589689,0.00001488624,0.0001176568,0.00003947879,0.9507918,0.01146674,0.01108722,0.0007185849,0.02541544],"study_design_scores_gemma":[0.000004215813,0.00002870274,0.00004208793,0.000004053481,0.000003282643,0.00002734048,0.00001133619,0.9941635,0.002462208,0.002175108,0.001074211,0.000003963567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05781469,0.0001222158,0.9249403,0.00008601467,0.00002647669,0.00003109635,0.00005106319,0.0004424688,0.0164857],"genre_scores_gemma":[0.7371839,0.0002317435,0.2499818,0.00006027689,0.00001493629,0.0001234756,0.0001133634,0.0002406258,0.01204987],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00278047,"threshold_uncertainty_score":0.009301603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01692536158112827,"score_gpt":0.1941724586258846,"score_spread":0.1772470970447563,"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."}}