{"id":"W2166868667","doi":"10.1109/aps.2007.4396795","title":"Evanescent field detection using negative refractive index lenses","year":2007,"lang":"en","type":"article","venue":"","topic":"Metamaterials and Metasurfaces Applications","field":"Materials Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Superlens; Evanescent wave; Optics; Refractive index; Sensitivity (control systems); Detector; Lens (geology); Field (mathematics); Materials science; Depth of field; Lossless compression; Optoelectronics; Physics; Computer science; Electronic engineering; Mathematics; Engineering","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":[0.0008264636,0.0008663607,0.0003501766,0.0005369441,0.0002143416,0.0007782172,0.0006026444,0.000493173,0.000542039],"category_scores_gemma":[0.00162289,0.0002929575,0.0001983432,0.0002473852,0.0009556828,0.001260238,0.0007972908,0.0003974781,0.0001768173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001125413,"about_ca_system_score_gemma":0.000279404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006756262,"about_ca_topic_score_gemma":0.0009479391,"domain_scores_codex":[0.9990591,0.0001974085,0.00004539373,0.0002336804,0.0004013005,0.00006305097],"domain_scores_gemma":[0.9982908,0.001007021,0.00036468,0.0001038484,0.0001790582,0.00005455573],"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":[0.0001222233,0.00003705179,0.0008654008,0.000119474,0.00001702322,0.00009452903,0.00006535557,0.001607886,0.9845095,0.003941975,0.00008469722,0.008534979],"study_design_scores_gemma":[0.000007670914,0.0001111532,0.001278532,0.00001090698,0.00001234078,0.0002402285,0.00002162085,0.01032907,0.9862006,0.0006948133,0.001069298,0.00002361452],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7216845,0.002993874,0.2623834,0.0003400503,0.00009657709,0.00008577752,0.0001157905,0.0003822037,0.01191782],"genre_scores_gemma":[0.9063295,0.001278193,0.08860831,0.0001933506,0.00004506244,0.0000542876,0.00007766876,0.00004401613,0.003369626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001125413,"threshold_uncertainty_score":0.008165479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03283732897857428,"score_gpt":0.3151112101155262,"score_spread":0.2822738811369519,"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."}}