{"id":"W2130846818","doi":"10.1017/s1431927609094744","title":"Quantitative Characterisation of Surface Defects and Composition on PtRu Nanoparticles Using Aberration-Corrected TEM/STEM","year":2009,"lang":"en","type":"article","venue":"Microscopy and Microanalysis","topic":"Advanced Materials Characterization Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; McMaster University","funders":"","keywords":"Materials science; Nanoparticle; Surface (topology); Composition (language); Nanotechnology; Chemical engineering; Geometry; Mathematics; Engineering","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":[0.00006988237,0.0001449162,0.000263213,0.000115374,0.00008035827,0.00004911433,0.00003404577,0.00006264734,0.000007864506],"category_scores_gemma":[0.000005374192,0.0001510867,0.00002902684,0.0001961413,0.00004027844,0.0002318813,0.000008827363,0.00004724077,0.000001443561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002883386,"about_ca_system_score_gemma":0.000004964686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007745069,"about_ca_topic_score_gemma":0.000001854473,"domain_scores_codex":[0.9993254,0.00004476716,0.0002841091,0.0001693523,0.00005855484,0.0001178374],"domain_scores_gemma":[0.9996629,0.00003292989,0.0001182843,0.0001045209,0.00004718173,0.0000342362],"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":[0.00004535305,0.00002155239,0.0003438824,0.00004180314,0.00002715177,5.029439e-7,0.0004224605,0.0008568476,0.9973494,0.00006321137,0.00000428676,0.0008235479],"study_design_scores_gemma":[0.0001475359,0.00008231385,0.004601277,0.0000790823,0.000072537,0.000003647169,0.0000558976,0.008838424,0.9859197,0.0000524299,0.000007197129,0.0001399777],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9825332,0.0001818406,0.01690552,0.00001763174,0.00004673331,0.0001424838,0.00003731854,0.000124424,0.00001084347],"genre_scores_gemma":[0.9890817,0.0001964819,0.01058893,0.00004045606,0.000008910813,0.000002208171,0.00006192856,0.00001421003,0.000005127363],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01142972,"threshold_uncertainty_score":0.6161138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.013724825346656,"score_gpt":0.2624765568867137,"score_spread":0.2487517315400577,"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."}}