{"id":"W2330329190","doi":"10.1109/jphot.2016.2548469","title":"Refractometric Sensing Using High-Order Diffraction Spots From Ordered Vertical Silicon Nanowire Arrays","year":2016,"lang":"en","type":"article","venue":"IEEE photonics journal","topic":"Photonic and Optical Devices","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Refractive index; Diffraction; Optics; Materials science; Optoelectronics; Silicon; Detector; Wavelength; Dispersion (optics); Nanowire; Diffraction efficiency; Spectrometer; Physics","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":[0.0002221584,0.0003194356,0.0003060064,0.0002726073,0.000113836,0.0003689521,0.0004948138,0.000373886,0.0004767435],"category_scores_gemma":[0.0003303936,0.0003623225,0.000216811,0.0003207432,0.0002739911,0.000607007,0.0003237953,0.0002362171,0.0003652173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002982421,"about_ca_system_score_gemma":0.0002000846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005299922,"about_ca_topic_score_gemma":0.001606953,"domain_scores_codex":[0.9997038,0.0000360697,0.00001879391,0.00006086823,0.000155081,0.00002528167],"domain_scores_gemma":[0.9997656,0.00007806806,0.00004917084,0.00003805641,0.00005313326,0.00001588235],"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":[0.00002081176,0.00001174186,0.000233079,0.00003464767,0.000003288916,0.00002859045,0.00001498422,0.0006737981,0.9929298,0.0003400166,0.00004802675,0.005661315],"study_design_scores_gemma":[0.000007391247,0.00007383319,0.0006710741,0.000002249281,0.00000362595,0.00008208762,0.00001413214,0.0124783,0.9857875,0.000194292,0.0006732,0.00001231731],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7932816,0.00127252,0.1982631,0.0002141407,0.0001500052,0.00007493996,0.0002840066,0.0005925721,0.005867233],"genre_scores_gemma":[0.802183,0.0008980993,0.1931799,0.00009417383,0.00004249178,0.00006383701,0.0001886638,0.00003629838,0.003313561],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005299922,"threshold_uncertainty_score":0.002163947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01708941401288557,"score_gpt":0.2395427219267593,"score_spread":0.2224533079138737,"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."}}