{"id":"W2102442524","doi":"10.1021/ac400785h","title":"FePt Alloy Nanoparticles for Biosensing: Enhancement of Vitamin C Sensor Performance and Selectivity by Nanoalloying","year":2013,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Electrochemical Analysis and Applications","field":"Chemistry","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Chemistry; Ascorbic acid; Overpotential; Nanoparticle; Alloy; Biosensor; X-ray photoelectron spectroscopy; Selectivity; Chemical engineering; Citric acid; Detection limit; Electrocatalyst; Catalysis; Inorganic chemistry; Nanotechnology; Nuclear chemistry; Electrochemistry; Electrode; Organic chemistry; Physical chemistry; Materials science; Chromatography","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":[0.00008016213,0.0001725242,0.0002849883,0.0000107036,0.00009981412,0.0000351643,0.0001153172,0.0001179388,0.0002186428],"category_scores_gemma":[0.00007660744,0.0001568013,0.0001028038,0.0001431893,0.0001442979,0.00006584215,0.00004904345,0.0001254317,0.000008706583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004215358,"about_ca_system_score_gemma":0.00002200886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001497662,"about_ca_topic_score_gemma":5.340005e-7,"domain_scores_codex":[0.9987835,0.000004062421,0.0003398324,0.0003731776,0.0001681765,0.0003312158],"domain_scores_gemma":[0.9992321,0.0001563304,0.0001099775,0.0002389854,0.0001149522,0.000147631],"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":[0.000009898493,0.0001499737,0.001158068,0.0002456831,0.00007640132,1.058776e-7,0.0000108521,0.000001137113,0.9952632,0.00002056896,0.001249936,0.001814144],"study_design_scores_gemma":[0.0002511396,0.00001606268,0.00003850112,0.00003076983,0.0000934702,0.000002817223,0.00004455545,0.01731904,0.9808679,0.00009137912,0.001062347,0.0001820355],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975818,0.00007370357,0.000174346,0.0003909553,0.00000202329,0.0000723972,0.00001224564,0.00002908913,0.001663421],"genre_scores_gemma":[0.9964113,0.00004627053,0.000676178,0.00005088144,0.00004173602,0.00005869424,0.00004282873,0.00001546576,0.002656693],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0173179,"threshold_uncertainty_score":0.6394172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007706370816556155,"score_gpt":0.2237837837544187,"score_spread":0.2160774129378626,"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."}}