{"id":"W3143185403","doi":"10.1109/cefc-06.2006.1633087","title":"Evolution of Wire Antennas in Three Dimensions using a Novel Growth Process","year":2006,"lang":"en","type":"article","venue":"","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Process (computing); Computer science; Antenna (radio); Implementation; Directional antenna; Reconfigurable antenna; Electronic engineering; Space (punctuation); Omnidirectional antenna; Engineering; Telecommunications; Antenna efficiency; Software engineering","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":[0.0002602299,0.0002934632,0.0002933116,0.000331872,0.0004114537,0.0008366741,0.0004704958,0.0008626969,0.001117735],"category_scores_gemma":[0.001292856,0.000228794,0.0005187075,0.0003866358,0.0008328886,0.0006195481,0.0007882148,0.0005497364,0.0002468075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003448547,"about_ca_system_score_gemma":0.0002451331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005721154,"about_ca_topic_score_gemma":0.0004610645,"domain_scores_codex":[0.9998958,0.00003055908,0.00000617793,0.00001761215,0.00003508769,0.00001477249],"domain_scores_gemma":[0.9995928,0.0002467851,0.00005592936,0.00004325449,0.00004131944,0.00001986863],"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":[0.00006632706,0.00009982943,0.001779096,0.0001066689,0.00003846819,0.00069942,0.0005333429,0.5992998,0.1066777,0.2468322,0.001134302,0.04273283],"study_design_scores_gemma":[0.00004011381,0.00009423038,0.0002972748,0.000009176621,0.00001258867,0.0002074416,0.00005469469,0.9464784,0.008922766,0.03899446,0.004867416,0.0000213831],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2830777,0.0004632977,0.6904141,0.0006839115,0.00008487687,0.00007352973,0.00005679586,0.0003054604,0.02484032],"genre_scores_gemma":[0.7403367,0.0006167286,0.2518772,0.00009166232,0.00002248984,0.0001573343,0.00006787894,0.00008613316,0.006743898],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001117735,"threshold_uncertainty_score":0.003739178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01795503862168674,"score_gpt":0.2494702710543048,"score_spread":0.2315152324326181,"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."}}