{"id":"W2581709982","doi":"10.1016/j.snb.2017.01.142","title":"Analysis of the heterogeneous structure of iron oxide/gold nanoparticles and their application in a nanosensor","year":2017,"lang":"en","type":"article","venue":"Sensors and Actuators B Chemical","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Universiti Sains Malaysia","keywords":"Nanosensor; Iron oxide nanoparticles; Zeta potential; Fourier transform infrared spectroscopy; Nanoparticle; Colloidal gold; Chemistry; Nuclear chemistry; X-ray photoelectron spectroscopy; Biosensor; Analytical Chemistry (journal); Materials science; Nanotechnology; Chemical engineering; 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":[0.0001819095,0.0001855156,0.00008891544,0.0002523306,0.0001598945,0.0001604737,0.000189055,0.0002867406,0.0005662237],"category_scores_gemma":[0.0002652419,0.0001511289,0.0001443993,0.0001108692,0.0001667687,0.0001554716,0.00009220397,0.00025129,0.0001303516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002541033,"about_ca_system_score_gemma":0.000109514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007797564,"about_ca_topic_score_gemma":0.001231204,"domain_scores_codex":[0.9998919,0.00001507053,0.000005648599,0.00002909934,0.00003658538,0.00002173217],"domain_scores_gemma":[0.9999069,0.0000265337,0.00001383242,0.000009533367,0.00002983227,0.00001344488],"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":[0.00002876154,0.00001017435,0.0001154794,0.000009732524,0.000002867025,0.00001492903,0.000007133347,0.00008637036,0.9990144,0.00005779276,0.00001188266,0.000640442],"study_design_scores_gemma":[0.000003224038,0.00004138323,0.001010766,9.760166e-7,0.000006096644,0.00002299513,0.000008049597,0.001802886,0.9968563,0.00001918788,0.0002265629,0.000001585335],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9895995,0.0005282034,0.008265644,0.000050041,0.00001490312,0.0000238905,0.00006924003,0.00002981995,0.001418843],"genre_scores_gemma":[0.9943013,0.0002051679,0.004412889,0.00002517005,0.000004960745,0.00001493958,0.00008524033,0.000007750699,0.0009425348],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007797564,"threshold_uncertainty_score":0.001894176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004621997693648234,"score_gpt":0.2360671609727319,"score_spread":0.2314451632790837,"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."}}