{"id":"W2489504623","doi":"10.1155/2016/2368630","title":"Silver Nanoparticles Embedded in Natural Rubber Films: Synthesis, Characterization, and Evaluation of<i>In Vitro</i>Toxicity","year":2016,"lang":"en","type":"article","venue":"Journal of Nanomaterials","topic":"Plant-Derived Bioactive Compounds","field":"Chemistry","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundação de Amparo à Pesquisa do Estado de São Paulo; American Physical Therapy Association","keywords":"Silver nanoparticle; Materials science; Silver nitrate; Nanoparticle; Natural rubber; Chemical engineering; Nanotechnology; Nuclear chemistry; Metal; Chinese hamster ovary cell; Metal ions in aqueous solution; Characterization (materials science); Chemistry; Composite material; Metallurgy","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":[0.001211103,0.0001384129,0.0004311331,0.0001490163,0.00001948975,0.00003322519,0.000141058,0.00009676597,0.0003351849],"category_scores_gemma":[0.0007493807,0.0000941984,0.00005047327,0.00008350853,0.00005470789,0.0004353326,0.00004040236,0.00005373924,0.000003144269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001266616,"about_ca_system_score_gemma":0.0001036752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003630707,"about_ca_topic_score_gemma":0.000004015908,"domain_scores_codex":[0.9983145,0.0002218217,0.0007726406,0.0001423767,0.0003683153,0.0001803394],"domain_scores_gemma":[0.9986019,0.0002830141,0.0007015999,0.0001230001,0.0002407958,0.00004968409],"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":[0.0005769412,0.00009396754,0.00400803,0.00003998456,0.00003199172,0.00001247848,0.0001265475,0.000001084361,0.9923344,0.000002040747,0.0000171678,0.002755342],"study_design_scores_gemma":[0.001348866,0.00001591039,0.04367622,0.0003330599,0.00004178555,0.00007650685,0.00004285785,0.00006261352,0.954152,0.00009051745,0.00004514915,0.0001145115],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992718,0.0001393505,0.000005501587,0.0001520205,0.0002268893,0.0000718841,0.00009168351,0.000006106763,0.00003473418],"genre_scores_gemma":[0.9995662,0.00008986834,0.0001912785,0.00001690117,0.00009360284,0.000007405491,0.000005624703,0.0000119825,0.00001713987],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03966819,"threshold_uncertainty_score":0.3841299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01909022336201932,"score_gpt":0.2578793109516552,"score_spread":0.2387890875896359,"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."}}