{"id":"W2730696354","doi":"10.1021/acs.molpharmaceut.7b00325","title":"Multiresponsive Nanogels for Targeted Anticancer Drug Delivery","year":2017,"lang":"en","type":"article","venue":"Molecular Pharmaceutics","topic":"Nanoparticle-Based Drug Delivery","field":"Materials Science","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"MacEwan University; University of Alberta","funders":"Grand Challenges Canada; Natural Sciences and Engineering Research Council of Canada; MacEwan University; National Natural Science Foundation of China; Canada Foundation for Innovation; University of Alberta; Alberta Innovates - Technology Futures","keywords":"Nanogel; Doxorubicin; Chemistry; Drug delivery; Concanavalin A; Cancer cell; Targeted drug delivery; Biophysics; Nanotechnology; Biochemistry; Cancer; Materials science; Biology; In vitro; Chemotherapy","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":[0.0001643755,0.0003329672,0.0001545958,0.0002107124,0.00008844146,0.0001935139,0.0001786252,0.0003708963,0.0007756489],"category_scores_gemma":[0.0001206024,0.0001722034,0.000194388,0.00007302969,0.0001530151,0.000281983,0.0002556091,0.0003713348,0.0002887182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003606854,"about_ca_system_score_gemma":0.0002049266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003364573,"about_ca_topic_score_gemma":0.0008781905,"domain_scores_codex":[0.9999107,0.00001080198,0.000008322553,0.00002276852,0.00003218303,0.00001513816],"domain_scores_gemma":[0.9999431,0.0000126829,0.00001632982,0.000004011514,0.00001158225,0.00001232792],"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":[0.000007388395,0.000004506802,0.0000096533,0.00002496853,0.000001509889,0.00001139538,0.000005268875,0.0000736387,0.9988815,0.0000980422,0.00002894771,0.0008531325],"study_design_scores_gemma":[0.000007234502,0.00008246581,0.0001463045,0.000004837955,0.000005426495,0.00008946424,0.00000549819,0.001286726,0.9958468,0.00005414035,0.002465594,0.00000549494],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9173267,0.01227076,0.06386501,0.0004609945,0.0002682894,0.000169821,0.0002990334,0.0006179802,0.004721417],"genre_scores_gemma":[0.9559621,0.002757205,0.03399282,0.0003439132,0.0000343952,0.0001311797,0.0002059322,0.00006910211,0.0065033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007756489,"threshold_uncertainty_score":0.002616942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03089573800892308,"score_gpt":0.331093876553003,"score_spread":0.30019813854408,"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."}}