{"id":"W2900327985","doi":"10.1109/jlt.2018.2875953","title":"Multichannel Long-Range Surface Plasmon Waveguides for Parallel Biosensing","year":2018,"lang":"en","type":"article","venue":"Journal of Lightwave Technology","topic":"Plasmonic and Surface Plasmon Research","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Biosensor; Materials science; Waveguide; Surface plasmon; Cascade; Etching (microfabrication); Optoelectronics; Fluidics; Plasmon; Optics; Optical filter; Surface plasmon polariton; Dynamic range; Surface plasmon resonance; Nanotechnology; Layer (electronics); Physics; Engineering; Electrical 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000513684,0.0002341201,0.0004868555,0.0005155873,0.0001229069,0.00003637783,0.0004073252,0.0004053286,0.00002993588],"category_scores_gemma":[0.0002874659,0.0001995281,0.0001532913,0.000405543,0.0002662387,0.0001671596,0.00006438536,0.0004908497,0.0000646777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001285287,"about_ca_system_score_gemma":0.00005934681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000296808,"about_ca_topic_score_gemma":0.00003673112,"domain_scores_codex":[0.9983013,0.00002252605,0.0006159355,0.0001774358,0.0002764649,0.0006063502],"domain_scores_gemma":[0.9986825,0.0002604784,0.0001644623,0.0002611408,0.0004995569,0.0001318909],"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":[0.002249039,0.0008156542,0.03707851,0.001008505,0.003410864,0.00202022,0.002629738,0.07650346,0.7182958,0.007704671,0.1248436,0.02343998],"study_design_scores_gemma":[0.003528428,0.001622992,0.0009543759,0.0002995293,0.0001058285,0.001190448,0.0005922596,0.3651163,0.592993,0.003616988,0.02925793,0.0007219556],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9681032,0.001068889,0.02746407,0.001438238,0.0008238051,0.0002294029,0.00001335068,0.0002315042,0.0006275849],"genre_scores_gemma":[0.9133899,0.0002818925,0.0859172,0.00002657691,0.00008028914,0.000002701852,0.000001317136,0.00005069807,0.0002494652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2886128,"threshold_uncertainty_score":0.8136522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02132579890755473,"score_gpt":0.2685637142007638,"score_spread":0.2472379152932091,"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."}}