{"id":"W1974031851","doi":"10.1049/iet-map.2009.0198","title":"Coarse models for efficient space mapping optimisation of microwave structures","year":2010,"lang":"en","type":"article","venue":"IET Microwaves Antennas & Propagation","topic":"Microwave Engineering and Waveguides","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Háskólinn í Reykjavík","keywords":"Space mapping; Representation (politics); Computer science; Convergence (economics); Surrogate model; Property (philosophy); Process (computing); Overhead (engineering); Computational complexity theory; Mathematical optimization; Algorithm; Quality (philosophy); Engineering design process; Mathematics; Engineering; Machine learning","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":[0.0005678074,0.0004740402,0.0006145964,0.0004541906,0.0002840794,0.0008823423,0.0006152326,0.0007499726,0.004202986],"category_scores_gemma":[0.00203591,0.0004767846,0.0006855257,0.0003723499,0.0005526232,0.0009762713,0.0009284764,0.0010602,0.0005187948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006016335,"about_ca_system_score_gemma":0.0006989177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002249215,"about_ca_topic_score_gemma":0.003055928,"domain_scores_codex":[0.999755,0.00007438372,0.000008455659,0.00001858384,0.0001219984,0.00002157555],"domain_scores_gemma":[0.9994992,0.0002954644,0.00003956609,0.0001083781,0.00004267397,0.00001477185],"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":[0.00002008738,0.0000114154,0.0001203206,0.0000286184,0.000005375997,0.00001768133,0.00003367836,0.97285,0.001989262,0.01244869,0.0002625765,0.01221243],"study_design_scores_gemma":[0.000004685284,0.00001367953,0.00004235355,0.000004418353,0.000002068925,0.000006125968,0.000005923109,0.9928018,0.0007495135,0.005085568,0.001280774,0.000003189244],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01329862,0.0001160206,0.9816426,0.00007752444,0.00001910711,0.00003352971,0.00005277977,0.0003594457,0.004400374],"genre_scores_gemma":[0.5912979,0.0003613725,0.4002354,0.00009288228,0.00002765077,0.0002522027,0.0002233862,0.0002828089,0.007226474],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004202986,"threshold_uncertainty_score":0.01406044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0126896729391024,"score_gpt":0.2124750887902485,"score_spread":0.1997854158511461,"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."}}