{"id":"W7018926546","doi":"","title":"Enhancing sensitivity for surface plasmon resonance using periodic structures and spectro-angular image analysis","year":2010,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Plasmonic and Surface Plasmon Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McGill University","keywords":"Resonance (particle physics); Surface plasmon resonance; Sensitivity (control systems); Surface plasmon; Energy (signal processing); Coupling (piping); Plasmon; Surface (topology)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004248425,0.0004095505,0.0003678914,0.0005049055,0.000209505,0.0006670678,0.0004704785,0.0005703997,0.002037295],"category_scores_gemma":[0.0007901363,0.0003605399,0.0003008262,0.0003786052,0.000382874,0.0005268737,0.0004770538,0.0006018316,0.0009434471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004786095,"about_ca_system_score_gemma":0.0002448941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003610487,"about_ca_topic_score_gemma":0.0006522052,"domain_scores_codex":[0.9995964,0.00005514496,0.00001125375,0.00009068599,0.0001984069,0.00004816209],"domain_scores_gemma":[0.9996862,0.0001354763,0.00003566422,0.00003371086,0.00009248794,0.00001643657],"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":[0.00003505421,0.0000520142,0.0001475769,0.0001087676,0.000008107389,0.00005789884,0.0000928432,0.00105398,0.9589266,0.002081391,0.0004989529,0.0369368],"study_design_scores_gemma":[0.0000167561,0.0001558761,0.00107594,0.00002590048,0.00001927651,0.0002637023,0.00004914672,0.01635775,0.9723771,0.001210363,0.008418528,0.0000295685],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.519706,0.009677694,0.4324098,0.001545195,0.0004118839,0.000249678,0.0001706204,0.001888658,0.03394054],"genre_scores_gemma":[0.6349971,0.005320107,0.3429707,0.0004751893,0.0001253855,0.0001577793,0.0001800927,0.0001578107,0.01561582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002037295,"threshold_uncertainty_score":0.006815374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01129699173743233,"score_gpt":0.2492778312340503,"score_spread":0.2379808394966179,"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."}}