{"id":"W2809395213","doi":"10.3390/photonics5030015","title":"Improved Magneto-Optic Surface Plasmon Resonance Biosensors","year":2018,"lang":"en","type":"article","venue":"Photonics","topic":"Plasmonic and Surface Plasmon Research","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Mitacs; York University; CMC Microsystems","keywords":"Materials science; Surface plasmon resonance; Biosensor; Optoelectronics; Plasmon; Wavelength; Surface plasmon; Bilayer; Photonics; Optics; Nanotechnology; Nanoparticle; Chemistry; Membrane","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002836818,0.0002541908,0.0002553682,0.00006624882,0.0001290275,0.00006390062,0.0003568168,0.0001793812,0.0003311178],"category_scores_gemma":[0.00007466804,0.0002550355,0.00007399466,0.0003553103,0.0001718239,0.0001339206,0.00007746458,0.0003964091,0.0009165904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001320643,"about_ca_system_score_gemma":0.00006361277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005553135,"about_ca_topic_score_gemma":0.0001090365,"domain_scores_codex":[0.998324,0.00002926911,0.0002685654,0.0003277932,0.0002987433,0.0007515879],"domain_scores_gemma":[0.9990454,0.0001465589,0.00002703027,0.0004893659,0.00009624336,0.0001954167],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006448585,0.0003202056,0.004682012,0.0005750022,0.000384693,0.0003161622,0.002655819,0.08050165,0.8309977,0.002334104,0.06721157,0.009376225],"study_design_scores_gemma":[0.0003672985,0.0001092665,0.000318449,0.00001860679,0.000007723324,0.00001315173,0.00005231228,0.8085765,0.1237933,0.00004485121,0.06641675,0.0002817919],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9801452,0.001245948,0.0001249036,0.0000786886,0.00056484,0.0002477419,0.00004846438,0.0004878576,0.01705635],"genre_scores_gemma":[0.9755795,0.0007165032,0.02019883,0.00005457273,0.00001947261,0.00001396281,0.000009641968,0.00008196251,0.003325565],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7280748,"threshold_uncertainty_score":0.9999902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01358410014109748,"score_gpt":0.2352552663900827,"score_spread":0.2216711662489852,"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."}}