{"id":"W2738067779","doi":"10.1139/cjc-2017-0203","title":"Exploring the in vivo toxicity of nanoparticles","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Chemistry","topic":"Anesthesia and Neurotoxicity Research","field":"Neuroscience","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"CYTED Ciencia y Tecnología para el Desarrollo; Ministerio de Economía y Competitividad","keywords":"Xenobiotic; Chemistry; In vivo; Toxicity; Biochemical engineering; Pharmacology; Risk analysis (engineering); Computational biology; Nanotechnology; Biotechnology; Biochemistry; Business; Biology; Engineering; Organic chemistry","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":[0.0004598903,0.0005297006,0.0003239182,0.0003084245,0.000185409,0.0002864548,0.0001876678,0.0004623882,0.001421733],"category_scores_gemma":[0.0004158108,0.0001683894,0.000452668,0.0001729307,0.0002477418,0.0003625263,0.00020728,0.0006701493,0.0004264131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002997875,"about_ca_system_score_gemma":0.0002866482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00092866,"about_ca_topic_score_gemma":0.001149833,"domain_scores_codex":[0.999747,0.00005702451,0.00001383334,0.00005723815,0.00008734428,0.00003754145],"domain_scores_gemma":[0.9997874,0.00007872575,0.00003886889,0.00001554629,0.00006606262,0.00001344165],"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":[0.0001385221,0.00006127053,0.000329073,0.0003745737,0.00002604467,0.00008842895,0.00003928695,0.0003006586,0.991396,0.0001864332,0.000266339,0.006793458],"study_design_scores_gemma":[0.000009276406,0.001707542,0.002373254,0.00005531675,0.0000782116,0.0003082315,0.00006045654,0.0008518315,0.9875405,0.0002331553,0.006769808,0.00001239654],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8823558,0.05424049,0.0395417,0.0005447149,0.0005647507,0.0003347849,0.0012175,0.0002819929,0.02091824],"genre_scores_gemma":[0.9246063,0.03970302,0.01929729,0.0005596001,0.0001295597,0.0004389798,0.001330904,0.0001305984,0.01380387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001421733,"threshold_uncertainty_score":0.004756153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1433506523097218,"score_gpt":0.2919902789632975,"score_spread":0.1486396266535758,"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."}}