{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004927032,0.0001728266,0.0002147905,0.00008717298,0.0002945405,0.00002043348,0.0001001691,0.000167899,0.00004076104],"category_scores_gemma":[0.00003677381,0.0001768757,0.00005752251,0.00006376717,0.0001502539,0.000114231,0.00004275164,0.0004111667,0.00005777679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007599159,"about_ca_system_score_gemma":0.00005401439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000801097,"about_ca_topic_score_gemma":0.000005460328,"domain_scores_codex":[0.9986862,0.0001509405,0.0002343696,0.0003344642,0.00008134378,0.000512696],"domain_scores_gemma":[0.9990547,0.0005798698,0.00004124458,0.0001180516,0.00004664967,0.0001594319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003853161,0.0005985702,0.001028659,0.002046353,0.001329702,0.0001407501,0.01962364,0.001968946,0.05805436,0.03631859,0.02883154,0.8496736],"study_design_scores_gemma":[0.001268961,0.0003143626,0.0008351488,0.0001153643,0.0001751089,0.00007799765,0.002376126,0.002702859,0.02061293,0.002234206,0.9688763,0.0004106517],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.591597,0.3586713,0.003347687,0.02827463,0.009338047,0.002036783,0.0005196654,0.0008501277,0.005364797],"genre_scores_gemma":[0.962779,0.03291862,0.001049703,0.0005182777,0.0005038736,0.00008328612,0.00001647346,0.00004182021,0.002088957],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9400448,"threshold_uncertainty_score":0.7212782,"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."}}