{"id":"W4400925918","doi":"10.1021/acsmaterialsau.4c00033","title":"Realizing the Potential of Commercial E-Textiles for Wearable Glucose Biosensing Application","year":2024,"lang":"en","type":"article","venue":"ACS Materials Au","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Alberta Innovates; Natural Sciences and Engineering Research Council of Canada; Government of Canada; University of Calgary","keywords":"Glucose oxidase; Chronoamperometry; Biosensor; Cyclic voltammetry; Detection limit; Electrode; Reproducibility; Amperometry; Wearable computer; Chemistry; Nanotechnology; Materials science; Electrochemistry; Biochemistry; Chromatography; Computer science; Embedded system","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":[0.0002714061,0.0001260633,0.0001966423,0.00004097562,0.0001013381,0.0001075495,0.0001092364,0.00006574736,0.00001355705],"category_scores_gemma":[0.000033954,0.0000981371,0.00003862337,0.00007791782,0.00004486544,0.000118017,0.00002737961,0.00003212072,0.00001403759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003401168,"about_ca_system_score_gemma":0.00001398448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001784385,"about_ca_topic_score_gemma":0.00001958678,"domain_scores_codex":[0.9992441,0.00002986582,0.000297105,0.0001376333,0.00007754438,0.0002137314],"domain_scores_gemma":[0.9996173,0.00009397851,0.00004099657,0.0001942517,0.00003025664,0.00002324981],"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":[0.00001708724,0.000003930841,5.488113e-7,0.000283403,0.00002342533,0.000001082615,0.0001235603,0.01670012,0.9736122,0.001896517,0.000264666,0.007073442],"study_design_scores_gemma":[0.00009315706,0.0000140104,0.0001309475,0.000116166,0.00003464876,0.00000843757,0.00003972133,0.002887952,0.9892094,0.002266976,0.005082791,0.0001158283],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9817735,0.0002646823,0.01541883,0.00009961741,0.001529236,0.000222317,0.0001010546,0.0002875307,0.0003032494],"genre_scores_gemma":[0.9979266,0.0001136981,0.00109066,0.00001712626,0.0006746064,0.00003583289,0.00004620148,0.0000515813,0.00004368372],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01615313,"threshold_uncertainty_score":0.4001915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01271051893413935,"score_gpt":0.243423594946215,"score_spread":0.2307130760120757,"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."}}