{"id":"W1972151680","doi":"10.1039/c4ra08944h","title":"Magnetic metrology for iron oxide nanoparticle scaled-up synthesis","year":2014,"lang":"en","type":"article","venue":"RSC Advances","topic":"Characterization and Applications of Magnetic Nanoparticles","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Metrology; Iron oxide nanoparticles; Nanoparticle; Iron oxide; Oxide; Magnetic nanoparticles; Nanotechnology; In situ; Materials science; Chemical engineering; Chemistry; Metallurgy; Engineering; Physics; Optics; Organic chemistry","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":[0.0001008616,0.0001056732,0.0001437922,0.00004380005,0.00006486166,0.00002346209,0.0001290142,0.00003623074,0.0001223862],"category_scores_gemma":[0.0001195376,0.0001040071,0.00003797349,0.0001136133,0.0000496733,0.000117735,0.00001364036,0.00003234745,0.00009795574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001371649,"about_ca_system_score_gemma":0.000003402465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000011281,"about_ca_topic_score_gemma":0.000008391035,"domain_scores_codex":[0.999341,0.00001757186,0.0001886652,0.00015654,0.00007093615,0.0002252535],"domain_scores_gemma":[0.9994302,0.0002493801,0.00002637756,0.0001994981,0.00002687982,0.00006760091],"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":[0.00002307454,0.00003981199,0.0005558663,0.00009575928,0.000006434179,1.618744e-7,0.00003895942,0.005057229,0.7254848,0.006178968,0.0005013406,0.2620176],"study_design_scores_gemma":[0.0006587942,0.0001204643,0.003932097,0.00001591916,0.00004980325,0.000004047176,0.00005208961,0.07181549,0.6285936,0.003067211,0.29137,0.0003204338],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9647418,0.000985918,0.03202858,0.0004821419,0.000195083,0.0002341887,0.00001337159,0.0003229247,0.0009959983],"genre_scores_gemma":[0.9933978,0.0001238777,0.005763019,0.00009749386,0.00007042102,0.0002915151,0.000004413639,0.00002349449,0.0002279871],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2908687,"threshold_uncertainty_score":0.4241286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006518961590617459,"score_gpt":0.2184912451339367,"score_spread":0.2119722835433192,"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."}}