{"id":"W2567163077","doi":"10.1021/acssensors.6b00763","title":"Surface Plasmon Resonance Clinical Biosensors for Medical Diagnostics","year":2016,"lang":"en","type":"article","venue":"ACS Sensors","topic":"Plasmonic and Surface Plasmon Research","field":"Engineering","cited_by":657,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Surface plasmon resonance; Nanotechnology; Biomolecule; Biosensor; Plasmon; Computer science; Medicine; Materials science; Optoelectronics; Nanoparticle","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":[],"consensus_categories":[],"category_scores_codex":[0.0009903022,0.0002571924,0.0004025606,0.00005908958,0.00008970768,0.00002607608,0.0003972512,0.000438594,0.0001474415],"category_scores_gemma":[0.003982672,0.0001852503,0.0001506973,0.0001812402,0.0002481236,0.0001092852,0.00007105119,0.0003408713,0.0006069934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007439852,"about_ca_system_score_gemma":0.00008270467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006982054,"about_ca_topic_score_gemma":0.0000301162,"domain_scores_codex":[0.9975036,0.00009549723,0.0005893665,0.0003970769,0.0006358459,0.0007785743],"domain_scores_gemma":[0.9925001,0.006497572,0.00004046881,0.0004168517,0.0001070006,0.0004380124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000702217,0.0004512429,0.1673399,0.000329616,0.0005524141,0.0007283745,0.0003487937,0.01972176,0.008325521,0.004394925,0.7157887,0.08131654],"study_design_scores_gemma":[0.005617491,0.0004173408,0.0187955,0.0004858545,0.00005635629,0.00006453812,0.0001524372,0.1747739,0.06328179,0.0005906599,0.7343525,0.001411662],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937984,0.0006254665,0.0007895448,0.001965082,0.000868116,0.0003158585,0.0001497834,0.000395061,0.001092631],"genre_scores_gemma":[0.9809303,0.01086607,0.00462772,0.0001251013,0.00009273897,0.00002195884,0.000009743166,0.0001028362,0.003223588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1550521,"threshold_uncertainty_score":0.7801875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03243732271552174,"score_gpt":0.3103639650435576,"score_spread":0.2779266423280359,"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."}}