{"id":"W4241387924","doi":"10.36227/techrxiv.11768823","title":"Metasurface Design Using Electromagnetic Inversion","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Antenna Design and Analysis","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; University of Manitoba","funders":"","keywords":"Inversion (geology); Solver; Computer science; Electromagnetic field; Finite-difference time-domain method; Inverse; Near and far field; Inverse problem; Scope (computer science); Set (abstract data type); Electronic engineering; Physics; Optics; Mathematics; Engineering; Mathematical analysis; Geometry; Geology","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":[0.0002619967,0.0004369665,0.0003368251,0.0002959063,0.0001400961,0.0006990297,0.0004936567,0.000646491,0.001587539],"category_scores_gemma":[0.0005365768,0.0001921196,0.0005379049,0.0001891207,0.000332999,0.0005592392,0.0006430672,0.0004664242,0.0005589142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004188518,"about_ca_system_score_gemma":0.0003182789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002021576,"about_ca_topic_score_gemma":0.0002110593,"domain_scores_codex":[0.9998562,0.0000268769,0.000004873399,0.00001609677,0.00008401914,0.00001190946],"domain_scores_gemma":[0.9998649,0.00004745918,0.0000176788,0.00003068763,0.00003205714,0.000007182629],"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":[0.0001201363,0.0000745363,0.0005561371,0.0002861217,0.00006630402,0.0002260214,0.0001366148,0.4018605,0.4158573,0.07685481,0.001268939,0.1026926],"study_design_scores_gemma":[0.00002362159,0.00009598352,0.0001359465,0.00002341448,0.00001223525,0.0002018586,0.00002302416,0.9134216,0.0684469,0.008223342,0.009376375,0.0000156733],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02543851,0.0001910023,0.9622539,0.0001568495,0.000054386,0.00004312556,0.0000456561,0.0003810857,0.01143544],"genre_scores_gemma":[0.4084558,0.0002674837,0.5857255,0.00008071156,0.00002604798,0.00009921142,0.0000898416,0.0001508214,0.005104481],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001587539,"threshold_uncertainty_score":0.005310833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05446033658097511,"score_gpt":0.2317861335327214,"score_spread":0.1773257969517463,"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."}}