{"id":"W3152065236","doi":"10.1109/cefc-06.2006.1633086","title":"Evolution of Two Dimensional Electromagnetic Devices using a Novel Genome Structure","year":2006,"lang":"en","type":"article","venue":"","topic":"Antenna Design and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Genetic algorithm; Genome; Genetic representation; Dual (grammatical number); Biology; Genetics; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00001761021,0.0000687592,0.00007357303,0.00006096095,0.00002108365,0.000006584433,0.00003418735,0.00003333672,0.0001358682],"category_scores_gemma":[0.000001256057,0.00006310233,0.00001940425,0.0001368332,0.00001227293,0.00006924144,0.000005635938,0.00003615175,0.000001540741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005561144,"about_ca_system_score_gemma":0.00001258625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001286007,"about_ca_topic_score_gemma":0.00006037116,"domain_scores_codex":[0.9996211,0.000003838139,0.0001201784,0.00006662047,0.00008027577,0.0001079861],"domain_scores_gemma":[0.9998693,0.000006753628,0.00001911406,0.00005502228,0.00003598854,0.00001386112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001228296,0.000003908348,0.0001893394,0.00000716287,0.000002765552,1.036448e-7,0.000003124459,0.4631716,0.5353826,0.001226943,0.00000536467,0.000005857145],"study_design_scores_gemma":[0.0002164359,0.00001636891,0.0108404,0.000006712949,0.00001404857,0.000009706376,0.000003851017,0.9834145,0.004878222,0.0005031114,0.00001146107,0.00008518447],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6567214,0.0003895491,0.3421859,0.000002352917,0.00003549262,0.00004911212,0.000004572926,0.00006274994,0.0005488597],"genre_scores_gemma":[0.9308379,7.596306e-7,0.06902713,0.000006648099,0.00004754285,4.135642e-7,0.00001342206,0.00001112612,0.00005503338],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5305043,"threshold_uncertainty_score":0.2573238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005917333894741959,"score_gpt":0.1893126848630987,"score_spread":0.1833953509683567,"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."}}