{"id":"W2581717273","doi":"10.1364/oe.25.001666","title":"Metal clad waveguide (MCWG) based imaging using a high numerical aperture microscope objective","year":2017,"lang":"en","type":"article","venue":"Optics Express","topic":"Photonic and Optical Devices","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Optics; Surface plasmon resonance; Numerical aperture; Materials science; Image resolution; Microscope; Surface plasmon; Depth of field; Biological imaging; Resolution (logic); Microscopy; Plasmon; Nanotechnology; Physics; Wavelength; Computer science; Nanoparticle","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002034235,0.0004322636,0.0001589043,0.0001364765,0.0001669362,0.0003024104,0.000356925,0.0003561605,0.0007974986],"category_scores_gemma":[0.000191384,0.0002211465,0.0001589001,0.000142518,0.0002542259,0.000351321,0.0002797385,0.0002966823,0.0002982617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007559716,"about_ca_system_score_gemma":0.0004858044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003171762,"about_ca_topic_score_gemma":0.006208372,"domain_scores_codex":[0.9999319,0.000005064119,0.000003359478,0.00001847762,0.00003339356,0.000007753828],"domain_scores_gemma":[0.9998778,0.00003875373,0.0000343945,0.00001859208,0.0000208144,0.000009517375],"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":[0.0000403129,0.00002569834,0.0003727429,0.00008942135,0.000008515423,0.00006905632,0.00004532094,0.02982226,0.9599333,0.002902253,0.0002650248,0.006426097],"study_design_scores_gemma":[0.0000143996,0.00005973452,0.0008483909,0.00001195517,0.000006218001,0.000102886,0.000013389,0.3596892,0.6346754,0.0004427658,0.004116773,0.00001893557],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5545604,0.0003310147,0.4317471,0.0001509085,0.00008984043,0.0001536623,0.0004463811,0.001151776,0.01136889],"genre_scores_gemma":[0.4661446,0.0003006134,0.528398,0.00004530082,0.000006817852,0.00008184173,0.0001957971,0.00009601907,0.00473109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003171762,"threshold_uncertainty_score":0.006306648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0124432494570679,"score_gpt":0.252270637561241,"score_spread":0.2398273881041731,"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."}}