{"id":"W2606854312","doi":"10.11159/icnnfc17.120","title":"Analytical Developments for the Characterization of Nanomaterials inConsumer Products, Environmental and Medicinal Samples","year":2017,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Recent Advances in Nanotechnology","topic":"Nanoparticles: synthesis and applications","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Horizon 2020","keywords":"Characterization (materials science); Nanomaterials; Nanotechnology; Materials science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003371498,0.001331394,0.0008341129,0.003335899,0.0005920638,0.0009668657,0.0008069936,0.001490726,0.00233625],"category_scores_gemma":[0.001884777,0.0004454402,0.0008095942,0.001081044,0.0009635882,0.001189337,0.001029819,0.001554736,0.001823625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005058802,"about_ca_system_score_gemma":0.001026071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003771414,"about_ca_topic_score_gemma":0.001197622,"domain_scores_codex":[0.9967951,0.000924753,0.0001915649,0.0007858976,0.001194564,0.0001081536],"domain_scores_gemma":[0.9983113,0.0005767979,0.0002027978,0.0002568484,0.0005771517,0.00007507314],"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":[0.00003431989,0.00009832218,0.001168321,0.0007140063,0.00006058927,0.0001144163,0.00006844639,0.0002375222,0.9055533,0.001692657,0.0006935338,0.08956455],"study_design_scores_gemma":[0.00001009193,0.0003205756,0.006097306,0.0001907241,0.0001148837,0.00177956,0.0001181531,0.003073636,0.8929698,0.003342734,0.09193393,0.00004848944],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08692614,0.07258471,0.8094743,0.001733851,0.0008627616,0.0007949528,0.00197819,0.001260609,0.02438458],"genre_scores_gemma":[0.1542919,0.03818397,0.788939,0.001542671,0.0005915885,0.0007942558,0.002183039,0.0002615669,0.01321187],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003371498,"threshold_uncertainty_score":0.01783037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01941295713939371,"score_gpt":0.27628959277687,"score_spread":0.2568766356374763,"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."}}