{"id":"W2026822060","doi":"10.1021/acsnano.5b01077","title":"A PEGylation-Free Biomimetic Porphyrin Nanoplatform for Personalized Cancer Theranostics","year":2015,"lang":"en","type":"article","venue":"ACS Nano","topic":"Nanoplatforms for cancer theranostics","field":"Engineering","cited_by":171,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research; Canada Foundation for Innovation; National Natural Science Foundation of China; Ontario Institute for Cancer Research; Prostate Cancer Canada; Congressionally Directed Medical Research Programs; Natural Sciences and Engineering Research Council of Canada; Princess Margaret Cancer Foundation","keywords":"PEGylation; Photodynamic therapy; Fluorescence-lifetime imaging microscopy; Biodistribution; Positron emission tomography; Drug delivery; Molecular imaging; Chemistry; Nanotechnology; Biophysics; Materials science; Fluorescence; Polyethylene glycol; Medicine; In vivo; Biochemistry; Nuclear medicine; In vitro; Biology","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":[0.00008498421,0.0002348705,0.0001193766,0.0001284514,0.0001022361,0.0001241008,0.0002054877,0.0003447914,0.0004962951],"category_scores_gemma":[0.0001132034,0.0001159817,0.0001267386,0.0000880793,0.0001412793,0.0002474977,0.0001964378,0.0002819276,0.000209372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003666276,"about_ca_system_score_gemma":0.0002016936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004577992,"about_ca_topic_score_gemma":0.0004828138,"domain_scores_codex":[0.9999444,0.000005428202,0.00000441122,0.00001907837,0.00001692512,0.000009661519],"domain_scores_gemma":[0.99997,0.000004129675,0.00001097123,0.00000397338,0.000005512394,0.000005492364],"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":[0.00002305743,0.00001039468,0.00004544585,0.00004546956,0.000002803275,0.00005400401,0.00001008827,0.0003482383,0.9927159,0.0003339434,0.00009914667,0.006311506],"study_design_scores_gemma":[0.00000816,0.0001178684,0.0003915647,0.00000424298,0.000007669258,0.0002547537,0.000004014621,0.004308722,0.9903445,0.00009446633,0.004456222,0.000007778799],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8455149,0.005783345,0.1424049,0.0005489265,0.0001419705,0.0002106628,0.0004002762,0.0008628856,0.004132162],"genre_scores_gemma":[0.9493182,0.001292776,0.04509202,0.0002002179,0.00001880739,0.00009985782,0.0001861532,0.0000359241,0.003755917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004962951,"threshold_uncertainty_score":0.002660096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03418861684974758,"score_gpt":0.2583933910528881,"score_spread":0.2242047742031405,"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."}}