{"id":"W2146116494","doi":"10.1109/iembs.2007.4353081","title":"Double Negative Metamaterials for Subsurface Detection","year":2007,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Metamaterials and Metasurfaces Applications","field":"Materials Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Metamaterial; Superlens; Evanescent wave; Optics; Homogeneous; Lossy compression; Transformation optics; Materials science; Penetration depth; Negative refraction; Physics; Computer science","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":[0.0001384227,0.0003931775,0.0001592367,0.0002003922,0.0001295777,0.0003747931,0.0001768025,0.000367782,0.0007713729],"category_scores_gemma":[0.0002025543,0.0001454698,0.0001135558,0.00009533688,0.0003122176,0.0004346908,0.0003121605,0.0003469965,0.0002678015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002162496,"about_ca_system_score_gemma":0.0001267721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005730245,"about_ca_topic_score_gemma":0.0001285371,"domain_scores_codex":[0.9999263,0.00001454586,0.000002520191,0.00001314807,0.00003144229,0.00001200877],"domain_scores_gemma":[0.9999115,0.00003531835,0.00001812054,0.00001185033,0.0000135989,0.000009593561],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000604961,0.00001401302,0.0001689854,0.0001039882,0.000003515813,0.00009182301,0.00003363681,0.0008530549,0.9632539,0.02117341,0.0002646159,0.0139785],"study_design_scores_gemma":[0.0000313195,0.0002658512,0.0006702825,0.00003654692,0.00001457183,0.0009454867,0.0000599687,0.03383277,0.9313718,0.01470107,0.01804022,0.00003018874],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7437826,0.0117551,0.2080881,0.0009544606,0.000355352,0.00006857628,0.00009938635,0.000607618,0.03428871],"genre_scores_gemma":[0.9437674,0.001875486,0.05079471,0.00008384263,0.00003596506,0.00002861752,0.00003260938,0.00002254223,0.003358748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007713729,"threshold_uncertainty_score":0.002580523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05464022005592633,"score_gpt":0.3051269830267579,"score_spread":0.2504867629708316,"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."}}