{"id":"W2515394036","doi":"10.1038/nmat4718","title":"Mechanism of hard-nanomaterial clearance by the liver","year":2016,"lang":"en","type":"article","venue":"Nature Materials","topic":"Graphene and Nanomaterials Applications","field":"Engineering","cited_by":981,"is_retracted":false,"has_abstract":false,"ca_institutions":"University Health Network; Canada Research Chairs; Toronto General Hospital; University of New Brunswick; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Hospital for Sick Children; Scheme for Promotion of Academic and Research Collaboration; University of Toronto; University of Galway; National University of Ireland","keywords":"Nanomaterials; Spleen; Phenotype; Mechanism (biology); Cell biology; Chemistry; Nanotechnology; Biophysics; Immunology; Biology; Materials science; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005823311,0.0005111112,0.0005621934,0.0006383552,0.0005052155,0.001264014,0.000819659,0.001030623,0.005310704],"category_scores_gemma":[0.0005591817,0.0002694992,0.0007897764,0.0001203699,0.0005798294,0.001314402,0.0008444359,0.000910576,0.001614467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007891651,"about_ca_system_score_gemma":0.000382085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003308816,"about_ca_topic_score_gemma":0.0001944012,"domain_scores_codex":[0.9995266,0.0001547308,0.00002027093,0.00008945038,0.00008310004,0.0001259339],"domain_scores_gemma":[0.9997031,0.00008089851,0.00005737198,0.00006512398,0.00004101298,0.00005253304],"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":[0.002414188,0.0003706519,0.005082925,0.001318918,0.0002778523,0.003656728,0.0003272892,0.001815327,0.8724056,0.0540551,0.005658431,0.05261687],"study_design_scores_gemma":[0.0001725961,0.001053309,0.008818734,0.0001209504,0.0001393909,0.004167986,0.0003007529,0.01771075,0.9267312,0.01734922,0.02335464,0.00008044916],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8591974,0.04042428,0.06620114,0.007009408,0.001152103,0.0003600259,0.00048266,0.0008996022,0.02427344],"genre_scores_gemma":[0.9867806,0.001908788,0.002894174,0.0004408971,0.00008711662,0.00004110062,0.00008973742,0.00002440748,0.007733073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005310704,"threshold_uncertainty_score":0.01776612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004608740550567914,"score_gpt":0.1873195160793508,"score_spread":0.1827107755287829,"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."}}