{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001728673,0.0003986731,0.0004151167,0.0002248837,0.0001512535,0.0003251521,0.0005030183,0.0008153016,0.0005292845],"category_scores_gemma":[0.0003075647,0.0002216128,0.0002386379,0.0001833339,0.0001697961,0.0003621632,0.0002506227,0.0002623791,0.0003452524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003475334,"about_ca_system_score_gemma":0.0001088273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008086301,"about_ca_topic_score_gemma":0.001399869,"domain_scores_codex":[0.9997687,0.00002626705,0.00001737533,0.00007408592,0.00009134136,0.00002227983],"domain_scores_gemma":[0.9999145,0.00002240543,0.00001873963,0.000008236511,0.00002360974,0.00001255653],"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":[0.00002502776,0.00000406097,0.00002789381,0.00002148429,0.000002268446,0.000009044298,0.000002973675,0.00002402866,0.9985293,0.00001417313,0.00001055924,0.0013292],"study_design_scores_gemma":[0.000002700211,0.00003655429,0.0002403785,0.000001359593,0.000004797314,0.00008585466,0.000002673256,0.000629443,0.9985127,0.000009418751,0.0004720106,0.000002117909],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9515524,0.009201527,0.03550394,0.000264974,0.00009691851,0.00007515468,0.0002844676,0.0005327947,0.002487956],"genre_scores_gemma":[0.9656163,0.001794662,0.02970595,0.0001085234,0.00001732344,0.00003245452,0.0002002244,0.00004132109,0.002483377],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008153016,"threshold_uncertainty_score":0.002521574,"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."}}