{"id":"W1965568849","doi":"10.1016/j.ijpharm.2014.01.010","title":"Image-based analysis of the size- and time-dependent penetration of polymeric micelles in multicellular tumor spheroids and tumor xenografts","year":2014,"lang":"en","type":"article","venue":"International Journal of Pharmaceutics","topic":"Nanoparticle-Based Drug Delivery","field":"Materials Science","cited_by":53,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Spheroid; Micelle; Penetration (warfare); HeLa; Nanoparticle; Nanomedicine; Biophysics; Drug delivery; Materials science; Cell culture; Distribution (mathematics); Cancer research; Cell; Biomedical engineering; Chemistry; Nanotechnology; In vitro; Medicine; Biology; 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":[0.0002018315,0.0002262891,0.0001741229,0.0004028418,0.0001314539,0.0001828372,0.000208503,0.0003324749,0.001206412],"category_scores_gemma":[0.0001723037,0.0001648168,0.0002318714,0.0003024891,0.0002008992,0.000286211,0.0001258117,0.0005019041,0.0002169522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003854559,"about_ca_system_score_gemma":0.0002171712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004162305,"about_ca_topic_score_gemma":0.002790797,"domain_scores_codex":[0.999927,0.000008510318,0.000004737555,0.00001734814,0.00002183286,0.00002049232],"domain_scores_gemma":[0.9998227,0.00006317641,0.0000358698,0.000009991376,0.00004433961,0.00002398192],"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":[0.00007808737,0.00001580983,0.00009954729,0.00002110086,0.000003031957,0.00001878418,0.00001625645,0.000138931,0.9988662,0.00005065889,0.00002343121,0.0006682607],"study_design_scores_gemma":[0.000007198887,0.00008734124,0.004882305,0.000002287624,0.00001395123,0.0000955774,0.00002092982,0.004880951,0.9896269,0.0000192504,0.0003559362,0.000007323831],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9827391,0.00096464,0.01303148,0.0001013627,0.0000233303,0.00006157334,0.0006650888,0.0001492536,0.002264248],"genre_scores_gemma":[0.9827456,0.0007963081,0.01236342,0.00006052896,0.00001169737,0.00007810554,0.0005103438,0.00006526809,0.003368768],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004162305,"threshold_uncertainty_score":0.008276165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01005647914022072,"score_gpt":0.2772524046980016,"score_spread":0.2671959255577809,"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."}}