{"id":"W2903367138","doi":"10.3390/polym10121317","title":"Smart Shear-Thinning Hydrogels as Injectable Drug Delivery Systems","year":2018,"lang":"en","type":"article","venue":"Polymers","topic":"Hydrogels: synthesis, properties, applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Shear thinning; Materials science; Swelling; Rheology; Self-healing hydrogels; Chemical engineering; Fourier transform infrared spectroscopy; Zeta potential; Nanocomposite; Gelatin; Composite material; Scanning electron microscope; Drug delivery; Rhodamine B; Chitosan; Polymer chemistry; Nanoparticle; Nanotechnology; Chemistry; Organic chemistry","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":[0.0001720635,0.0003546983,0.0001805425,0.0002259093,0.00006226863,0.0001656983,0.000111625,0.0001965189,0.0005576153],"category_scores_gemma":[0.00009757814,0.000157933,0.0001666348,0.00009455147,0.0001283958,0.0002712107,0.0001441398,0.000364122,0.0001994406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001348801,"about_ca_system_score_gemma":0.0000969068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001061875,"about_ca_topic_score_gemma":0.0002594391,"domain_scores_codex":[0.9999458,0.000008405595,0.000005411158,0.00001276765,0.00001733849,0.00001037636],"domain_scores_gemma":[0.9999173,0.00001494186,0.00003682642,0.000003543063,0.000009327182,0.00001810132],"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":[0.00001365347,0.000006950131,0.000016042,0.00002777429,0.000001956212,0.00001810775,0.000004125588,0.00008527397,0.9988849,0.00005835017,0.000008946684,0.0008739181],"study_design_scores_gemma":[0.000009986385,0.0001939566,0.0004296666,0.000005383799,0.00001119899,0.0001072658,0.000004102302,0.001418578,0.9964359,0.00003219847,0.001346725,0.000005173442],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9744859,0.00445545,0.01837118,0.0001256401,0.00007362289,0.00007260642,0.0001567735,0.0001901292,0.002068582],"genre_scores_gemma":[0.9797553,0.001997622,0.01599566,0.00009376586,0.00003418698,0.0000478564,0.0001121511,0.00002467384,0.001938812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005576153,"threshold_uncertainty_score":0.001865387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.012321820342787,"score_gpt":0.2351537993491348,"score_spread":0.2228319790063478,"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."}}