{"id":"W2646663540","doi":"10.1007/s00216-017-0427-2","title":"Results of an interlaboratory method performance study for the size determination and quantification of silver nanoparticles in chicken meat by single-particle inductively coupled plasma mass spectrometry (sp-ICP-MS)","year":2017,"lang":"en","type":"article","venue":"Analytical and Bioanalytical Chemistry","topic":"Nanoparticles: synthesis and applications","field":"Materials Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centre for Ecology and Hydrology; Seventh Framework Programme; Universidad de Zaragoza; Joint Research Centre; Istituto Superiore di Sanità; European Commission; Arizona State University","keywords":"Repeatability; Reproducibility; Inductively coupled plasma mass spectrometry; Particle size; Chemistry; Mass spectrometry; Particle (ecology); Analytical Chemistry (journal); Chromatography; European union; Nanoparticle; Detection limit; Materials science; Nanotechnology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.04225055,0.002661229,0.001285174,0.002833368,0.00241143,0.002525554,0.001917938,0.00333719,0.001288633],"category_scores_gemma":[0.04863287,0.001503227,0.00240934,0.002218624,0.002908316,0.0007680108,0.002137966,0.001662805,0.001413204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002306927,"about_ca_system_score_gemma":0.00318335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008667558,"about_ca_topic_score_gemma":0.00893068,"domain_scores_codex":[0.9316482,0.02170861,0.005598264,0.01390919,0.02600391,0.001131901],"domain_scores_gemma":[0.9603276,0.015558,0.003532433,0.007937507,0.01178208,0.0008624273],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.005068079,0.003113618,0.0679402,0.001055466,0.002277523,0.0004604726,0.004128083,0.006653293,0.8327888,0.001194076,0.002112968,0.07320753],"study_design_scores_gemma":[0.0008059668,0.01742215,0.2145344,0.0003277727,0.001967084,0.003001217,0.001058403,0.02066559,0.7181293,0.00159488,0.01991826,0.0005749253],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.650005,0.005415819,0.3230518,0.0009739438,0.0007776362,0.004273485,0.003658625,0.002443179,0.00940043],"genre_scores_gemma":[0.8005214,0.001054967,0.1803778,0.001716749,0.0001437488,0.003948867,0.005759089,0.0007471217,0.005730258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9577494,"threshold_uncertainty_score":0.223445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03244342580606237,"score_gpt":0.3047277696797167,"score_spread":0.2722843438736543,"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."}}