{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009801429,0.0002609827,0.0003655477,0.000102014,0.00003250476,0.00005891966,0.0002264975,0.0001789176,0.0003146919],"category_scores_gemma":[0.00001409388,0.0002536428,0.0001838459,0.0002081527,0.00001568073,0.00003824844,0.0001316677,0.0004193213,0.0001298968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008641531,"about_ca_system_score_gemma":0.00003972651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000432731,"about_ca_topic_score_gemma":0.000001227018,"domain_scores_codex":[0.9990652,0.00005711763,0.0002043756,0.0002795964,0.0001653508,0.0002283989],"domain_scores_gemma":[0.9995601,0.00002655925,0.00003228131,0.00024649,0.00002748934,0.0001071138],"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":[0.00000589261,0.000007313606,0.0000101051,0.0001715292,0.0003605565,0.00002552328,0.0000847429,0.2157503,0.7802963,0.00004906598,0.002934512,0.0003041818],"study_design_scores_gemma":[0.00006234069,0.00001795942,0.000006249523,0.00003258062,0.000285542,0.000001656881,0.00002198579,0.9893274,0.009048542,0.0007864719,0.0001241294,0.0002851539],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009137381,0.001387998,0.9874079,0.0000962802,0.0001409899,0.0001557196,0.00000294428,0.0005852624,0.001085521],"genre_scores_gemma":[0.8372337,0.0004186804,0.1617312,0.0001236036,0.0000762877,0.000005118291,0.00001744913,0.00006817825,0.000325842],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8280963,"threshold_uncertainty_score":0.9999916,"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."}}