{"id":"W2757107476","doi":"10.3390/app7100973","title":"A Review of Three-Dimensional Scanning Near-Field Optical Microscopy (3D-SNOM) and Its Applications in Nanoscale Light Management","year":2017,"lang":"en","type":"review","venue":"Applied Sciences","topic":"Near-Field Optical Microscopy","field":"Engineering","cited_by":115,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Near-field scanning optical microscope; Materials science; Aperture (computer memory); Optical microscope; Optics; Plasmon; Near and far field; Nanophotonics; Nanotechnology; Optoelectronics; Scanning electron microscope; Physics; Acoustics","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":[0.000746768,0.001113252,0.0009776456,0.003577694,0.0004562702,0.0009904329,0.001101515,0.001542792,0.004816182],"category_scores_gemma":[0.000785636,0.0005812869,0.0005329997,0.003705291,0.0006494181,0.002186822,0.0009342298,0.001474978,0.002723218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006941116,"about_ca_system_score_gemma":0.001060121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001169951,"about_ca_topic_score_gemma":0.001647237,"domain_scores_codex":[0.9996914,0.00003969888,0.00003959778,0.00006679606,0.0001366748,0.00002592162],"domain_scores_gemma":[0.9994372,0.0002735731,0.00007565934,0.00002674003,0.0001467076,0.00004018068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002910574,0.00007037234,0.0002239237,0.01898442,0.00005149429,0.0002051689,0.00008412296,0.0007439953,0.006996462,0.01238313,0.02501593,0.935212],"study_design_scores_gemma":[0.00000339656,0.00006437303,0.0004064128,0.001502451,0.00004049655,0.001156198,0.00003949839,0.0002621004,0.002351488,0.00168715,0.9924539,0.00003259054],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001744086,0.9953247,0.001457318,0.0001992101,0.0002730837,0.00000909831,0.00002468427,0.00002275931,0.002514636],"genre_scores_gemma":[0.001210673,0.995204,0.001712463,0.0002033558,0.0002901766,0.00001708323,0.00004967387,0.000006454793,0.001306141],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004816182,"threshold_uncertainty_score":0.01611173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03894157708813479,"score_gpt":0.3343472206637215,"score_spread":0.2954056435755867,"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."}}