{"id":"W2073685731","doi":"10.1016/j.msec.2014.11.046","title":"MIL-53(Fe), MIL-101, and SBA-15 porous materials: Potential platforms for drug delivery","year":2014,"lang":"en","type":"article","venue":"Materials Science and Engineering C","topic":"Nanoparticle-Based Drug Delivery","field":"Materials Science","cited_by":152,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Drug delivery; Nanotechnology; Porosity; Drug; Composite material; Pharmacology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003059029,0.0003574144,0.0004759735,0.000237448,0.0004432166,0.0008692548,0.0004686756,0.0001010642,0.0001243118],"category_scores_gemma":[0.0002944908,0.0003123276,0.00003173681,0.0002421776,0.0004240285,0.001035521,0.0003063436,0.00005759809,0.00007305998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008171465,"about_ca_system_score_gemma":0.0001042724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001677459,"about_ca_topic_score_gemma":0.000006812705,"domain_scores_codex":[0.9971411,0.00003017289,0.000529089,0.0007596912,0.0005358586,0.001004104],"domain_scores_gemma":[0.9988273,0.000118304,0.0001368071,0.0004090545,0.0001893047,0.0003192114],"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":[0.00009323251,0.0000255299,0.0000170283,0.0001710508,0.000004529908,0.00000652054,0.0001721931,0.0003652587,0.9979495,0.00048399,0.0002964244,0.0004147476],"study_design_scores_gemma":[0.0007840899,0.0001312035,0.0008753266,0.00007706566,0.0000340443,0.00005469579,0.00006481286,0.002531096,0.9940853,0.0003309316,0.0005842869,0.0004471847],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954008,0.0001670644,0.001003806,0.0001411727,0.002450438,0.0004404194,0.0001440141,0.0002371684,0.0000150643],"genre_scores_gemma":[0.994868,0.00004338955,0.004344502,0.0001503658,0.0004075003,0.00007677303,0.00001277321,0.00004585566,0.00005079657],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003864232,"threshold_uncertainty_score":0.9999329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006662783087358501,"score_gpt":0.1962174679620779,"score_spread":0.1895546848747194,"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."}}