{"id":"W4394627366","doi":"10.1039/d3sd00333g","title":"Large-scale validation of a plasmonic sensor for SARS-CoV-2 pseudo-neutralization with a cohort of food and retail workers","year":2024,"lang":"en","type":"article","venue":"Sensors & Diagnostics","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Infection and Immunity; National Research Council Canada; Institut National de Santé Publique du Québec; Centre hospitalier universitaire de Québec; University of Ottawa; PROTEO; Université de Montréal; Université Laval; Regroupement Québécois sur les Matériaux de Pointe","funders":"Natural Sciences and Engineering Research Council of Canada; National Research Council Canada; Public Health Agency; Public Health Agency of Canada","keywords":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Scale (ratio); Cohort; Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Neutralization; Virology; Medicine; Environmental health; Business; Geography; Internal medicine; Virus; Cartography","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":[0.0002514584,0.0001746805,0.0003534311,0.0002053129,0.0000447622,0.00002393867,0.00003494734,0.0001276755,0.000003398418],"category_scores_gemma":[0.0009489348,0.0001522856,0.00008207945,0.0004503148,0.00009956246,0.00007651153,0.00001628094,0.0001361947,0.000002932344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003932661,"about_ca_system_score_gemma":0.00008931383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000261269,"about_ca_topic_score_gemma":0.00004361943,"domain_scores_codex":[0.99879,0.00003880047,0.0004010082,0.0003010771,0.0002446621,0.0002244542],"domain_scores_gemma":[0.9984382,0.0008899494,0.000151683,0.0002003333,0.0002825465,0.00003724237],"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":[0.0006842109,0.0003502505,0.2878534,0.00238652,0.0006736488,0.00005322708,0.003198053,0.0002991195,0.7019836,0.0006448235,0.0009073331,0.0009658542],"study_design_scores_gemma":[0.001297309,0.001060058,0.00546588,0.0009325847,0.0006604074,0.0001236109,0.0005884752,0.01469365,0.9743093,0.0000972042,0.0006136749,0.0001578409],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992651,0.0002802286,0.005553694,0.00014165,0.0001505049,0.0008495909,0.00008482352,0.0001215109,0.0001669681],"genre_scores_gemma":[0.9931383,0.00008594785,0.006414841,0.0001219854,0.00006572608,0.00003201883,0.00003956984,0.00005238452,0.00004924776],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2823875,"threshold_uncertainty_score":0.6210027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0278078753019409,"score_gpt":0.2853633994813592,"score_spread":0.2575555241794183,"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."}}