{"id":"W2032688709","doi":"10.1073/pnas.1001367107","title":"In vivo assembly of nanoparticle components to improve targeted cancer imaging","year":2010,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Nanoparticle-Based Drug Delivery","field":"Materials Science","cited_by":179,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Toronto; Natural Sciences and Engineering Research Council of Canada; University Health Network; Canadian Institutes of Health Research; Ontario Innovation Trust","keywords":"In vivo; Nanoparticle; Molecular imaging; Nanotechnology; Pharmacokinetics; Chemistry; Biophysics; Materials science; Pharmacology; Medicine; 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":[0.0004677592,0.0005315451,0.0002673487,0.0001854661,0.000208819,0.0003882491,0.0002515177,0.0005647837,0.001007104],"category_scores_gemma":[0.0003033454,0.0003385046,0.0002524025,0.0000825891,0.0002461742,0.0003026131,0.0002432843,0.0007774608,0.0005353765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004406915,"about_ca_system_score_gemma":0.0002058488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004692289,"about_ca_topic_score_gemma":0.0008515416,"domain_scores_codex":[0.9997109,0.00009046029,0.00001742826,0.00007329079,0.00006893173,0.00003911773],"domain_scores_gemma":[0.9998735,0.00002804763,0.00004339436,0.00001847351,0.00002005621,0.00001647735],"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":[0.00001026272,0.00002153717,0.00002881332,0.00001316014,0.000002413223,0.000009262298,0.00001070043,0.0001073443,0.9986936,0.000100819,0.00003536938,0.0009667855],"study_design_scores_gemma":[0.000003766639,0.00007424475,0.0001725217,0.000001252621,0.000007452904,0.00004702144,0.000002731321,0.001059937,0.9963607,0.00001568046,0.002253144,0.000001531318],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7487271,0.003157399,0.239608,0.0005872092,0.0002527759,0.0002593557,0.0001281306,0.0009500104,0.006329959],"genre_scores_gemma":[0.8888824,0.001358261,0.09899243,0.0003408549,0.00005434768,0.0001356454,0.0002624867,0.0002209551,0.009752658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001007104,"threshold_uncertainty_score":0.003369093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02104220169447938,"score_gpt":0.2954343760415778,"score_spread":0.2743921743470984,"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."}}