{"id":"W2977756156","doi":"10.1002/adhm.201900898","title":"Rational Design of Rapidly Separating Dissolving Microneedles for Precise Drug Delivery by Balancing the Mechanical Performance and Disintegration Rate","year":2019,"lang":"en","type":"article","venue":"Advanced Healthcare Materials","topic":"Advancements in Transdermal Drug Delivery","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Higher Education Discipline Innovation Project; Traditional Chinese Medicine Bureau of Guangdong Province; Postdoctoral Research Foundation of China; National Natural Science Foundation of China","keywords":"Rational design; Materials science; Drug delivery; Skin irritation; Biomedical engineering; Dissolution; In vivo; Drug; Nanotechnology; Polymer; Permeation; Pharmacology; Chemistry; Composite material; Medicine; Membrane; Dermatology; Organic chemistry; Biology","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":[0.0002581942,0.0003982155,0.0002552504,0.0002597276,0.000124086,0.0002792889,0.0001837201,0.0002767665,0.000327402],"category_scores_gemma":[0.0002475466,0.0002079882,0.0002512558,0.0001481057,0.0001587214,0.0003890099,0.0002088355,0.0003112921,0.0001685717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004004269,"about_ca_system_score_gemma":0.0003718532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004602326,"about_ca_topic_score_gemma":0.0009202562,"domain_scores_codex":[0.9998676,0.00001706936,0.00001574059,0.00003242771,0.00004655859,0.0000205399],"domain_scores_gemma":[0.99993,0.00001244017,0.00002869829,0.000003451882,0.00001504734,0.00001029526],"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":[0.00004156356,0.00002959445,0.0001127599,0.0001590778,0.000007640696,0.00004114783,0.00001846876,0.001724283,0.9893924,0.0008769719,0.0000619196,0.007534175],"study_design_scores_gemma":[0.00003273974,0.0005051256,0.0007690429,0.00002068488,0.00003107515,0.00009447952,0.00002281891,0.01196094,0.9801241,0.0002090211,0.006208091,0.00002186666],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9127735,0.007864184,0.07450333,0.000275136,0.00006088644,0.0003386532,0.0001572796,0.0001980956,0.003828878],"genre_scores_gemma":[0.9124289,0.004819206,0.08041757,0.0001147073,0.00001514844,0.0002453827,0.0001401145,0.00002761916,0.001791313],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004602326,"threshold_uncertainty_score":0.002905309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05013301554344144,"score_gpt":0.3865974334439826,"score_spread":0.3364644179005412,"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."}}