{"id":"W2118455916","doi":"10.1039/c5an00694e","title":"Plasmonic sensors for the competitive detection of testosterone","year":2015,"lang":"en","type":"article","venue":"The Analyst","topic":"Gold and Silver Nanoparticles Synthesis and Applications","field":"Materials Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Institut Mérieux; Université de Montréal; Canada Foundation for Innovation","keywords":"Biosensor; Plasmon; Nanotechnology; Chemistry; Key (lock); Testosterone (patch); Biochemical engineering; Environmental chemistry; Computational biology; Computer science; Materials science; Biology; Optoelectronics; Engineering; Endocrinology","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":[0.0003987714,0.00004119753,0.00007961575,0.00001103094,0.0001291301,0.00002011749,0.0001527788,0.00001209259,0.00001608263],"category_scores_gemma":[0.00003874339,0.00001977046,0.00004307644,0.00009589914,0.00009186411,0.00002814433,0.00002120054,0.0000203293,0.00004643878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001004348,"about_ca_system_score_gemma":0.00001399719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009733452,"about_ca_topic_score_gemma":0.00009542182,"domain_scores_codex":[0.9995943,0.00003744799,0.0001165956,0.00007450974,0.00009117609,0.00008593823],"domain_scores_gemma":[0.9993452,0.0002832091,0.00007237172,0.0002041527,0.00007197324,0.00002302596],"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":[0.00001858051,0.00001812724,0.00006028285,0.000001731406,0.000009012228,3.660121e-8,0.0002558857,0.0003406584,0.9959034,0.00271901,0.00009961856,0.0005737124],"study_design_scores_gemma":[0.0001248744,0.00003983749,0.0008320334,0.000003919483,0.00006652049,0.000001359816,0.001214912,0.002021633,0.9914343,0.0004036369,0.003824868,0.00003205197],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976245,0.0001090299,0.0008688711,0.000876461,0.00004372591,0.0001475231,0.00001386048,0.00001189961,0.0003041781],"genre_scores_gemma":[0.9996591,0.000005440248,0.0000898837,0.00003796974,0.00003863442,0.00003398104,6.266936e-7,0.000003398723,0.0001309284],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004468991,"threshold_uncertainty_score":0.09931771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04098419228655971,"score_gpt":0.2588859973030702,"score_spread":0.2179018050165105,"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."}}