{"id":"W4391770766","doi":"10.1021/acssensors.3c02279","title":"Microneedle Assays for Continuous Health Monitoring: Challenges and Solutions","year":2024,"lang":"en","type":"article","venue":"ACS Sensors","topic":"Advancements in Transdermal Drug Delivery","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Continuous monitoring; Risk analysis (engineering); Computer science; Remote patient monitoring; Transdermal; Nanotechnology; Systems engineering; Biochemical engineering; Medicine; Engineering; Operations management; Materials science","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":[0.006462237,0.001272282,0.001443666,0.001551055,0.0007475213,0.003496763,0.001884752,0.004280618,0.001567204],"category_scores_gemma":[0.006580782,0.0009319675,0.0006805751,0.0009667879,0.001850779,0.00348175,0.00214238,0.004262027,0.001301143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001338218,"about_ca_system_score_gemma":0.001720498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001077575,"about_ca_topic_score_gemma":0.001910859,"domain_scores_codex":[0.9938788,0.001400198,0.0003473851,0.0008133891,0.003300021,0.0002602027],"domain_scores_gemma":[0.9929072,0.003135092,0.0008369408,0.0004575485,0.002333943,0.0003293456],"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":[0.0001925811,0.0003547977,0.004039584,0.007932145,0.0001696223,0.0007844885,0.0007518599,0.004605204,0.4801491,0.03234271,0.02287307,0.4458048],"study_design_scores_gemma":[0.00006738,0.001476943,0.004496093,0.002376075,0.0001894036,0.0063207,0.002009327,0.03312704,0.4423809,0.05632341,0.4508537,0.0003789628],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.03064011,0.5296092,0.3528736,0.06551182,0.003487251,0.0005956523,0.0005673421,0.001025651,0.01568938],"genre_scores_gemma":[0.2267133,0.402976,0.338524,0.01290482,0.002868621,0.001292248,0.0009144483,0.000181008,0.0136256],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006462237,"threshold_uncertainty_score":0.03417593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2333205297208781,"score_gpt":0.4595071865605098,"score_spread":0.2261866568396317,"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."}}