{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002279696,0.0002270206,0.000371856,0.00007908348,0.0003322294,0.0003848665,0.0003376648,0.0001236831,0.000687578],"category_scores_gemma":[0.0001571957,0.0001972701,0.00007414984,0.0002066412,0.000111189,0.0004684403,0.00006599946,0.00005883364,0.0002406489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004845798,"about_ca_system_score_gemma":0.00004931448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007807455,"about_ca_topic_score_gemma":0.0000351754,"domain_scores_codex":[0.9982207,0.000009459979,0.0005146677,0.0005038414,0.0002359663,0.0005153907],"domain_scores_gemma":[0.9985363,0.00009053612,0.0003344756,0.0001615178,0.0007211833,0.0001559652],"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":[0.0002579782,0.00002830907,0.00005214463,0.00006507378,0.000009187353,1.423501e-7,0.000642803,0.000001031754,0.9880996,0.00993358,0.0001112882,0.0007988311],"study_design_scores_gemma":[0.0007337794,0.00008373647,0.0005432045,0.00001839462,0.00005491394,0.000005054233,0.0005109132,0.00007082058,0.9828429,0.004680878,0.01021352,0.0002418608],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9560753,0.00003979397,0.03954053,0.0001340443,0.0007074395,0.001091091,0.00003898526,0.0002064393,0.002166399],"genre_scores_gemma":[0.9798124,0.00001693388,0.01896133,0.00005924849,0.0001840237,0.0003077834,0.000007144271,0.00002808753,0.0006230709],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02373709,"threshold_uncertainty_score":0.8044441,"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."}}