{"id":"W3162239383","doi":"10.1002/slct.202100354","title":"In‐Silico Tuning of Curcumin Loading on PEG Grafted Chitosan: An Atomistic Simulation","year":2021,"lang":"en","type":"article","venue":"ChemistrySelect","topic":"Polysaccharides Composition and Applications","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Amirkabir University of Technology","keywords":"Curcumin; Polyethylene glycol; Biocompatibility; Chitosan; PEG ratio; Drug delivery; Materials science; Polymer; Chemical engineering; PEG 400; Chemistry; Nanotechnology; Organic chemistry; Composite material; Biochemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003383958,0.0004898643,0.0005794654,0.0005466903,0.0006745816,0.0005274852,0.0008122261,0.001429924,0.00353749],"category_scores_gemma":[0.001030704,0.0004694005,0.0007839234,0.0004358002,0.0004691637,0.0003658989,0.0003390833,0.0006646253,0.0001755208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001055288,"about_ca_system_score_gemma":0.001175037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02461037,"about_ca_topic_score_gemma":0.0182267,"domain_scores_codex":[0.9999218,0.00002070998,0.000003159724,0.00001043232,0.00001948214,0.0000244273],"domain_scores_gemma":[0.9992867,0.0005203883,0.00004899094,0.00002407382,0.00008213168,0.00003778473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007143358,0.0000588059,0.001152436,0.00004725227,0.00003070679,0.00008344989,0.00002847871,0.9950644,0.001460421,0.0008281312,0.0002708605,0.0009034869],"study_design_scores_gemma":[0.00001441554,0.00001529487,0.0002038163,0.000003387704,0.000005701323,0.000004483606,0.00001147721,0.9992294,0.0002546341,0.0001278095,0.0001264056,0.000003203173],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9508514,0.0003673962,0.02778238,0.0006387446,0.00010445,0.0001239362,0.0009112881,0.0003087526,0.01891169],"genre_scores_gemma":[0.9891003,0.0001259777,0.008571851,0.00008304383,0.000009947109,0.0001187559,0.0003129675,0.0000465453,0.001630579],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02461037,"threshold_uncertainty_score":0.04893422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02345168020664831,"score_gpt":0.2732421773330479,"score_spread":0.2497904971263996,"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."}}