{"id":"W4389037238","doi":"10.1002/anse.202300064","title":"An Optofluidic System for Monitoring Fluorescently Activated Protein Biomarkers","year":2023,"lang":"en","type":"article","venue":"Analysis & Sensing","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fluorophore; Bovine serum albumin; Microfluidics; Fluorescence; Fluorescein isothiocyanate; Fluorescein; Chemistry; Nanotechnology; Materials science; Biophysics; Chromatography; Biology; Optics","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":[0.0005339816,0.0004243946,0.0002285193,0.0004087538,0.0003640866,0.0004427271,0.0006184926,0.0008081544,0.0008074978],"category_scores_gemma":[0.0004706236,0.0002577692,0.0001791231,0.0002344258,0.000328651,0.0003407877,0.0002777835,0.0005346653,0.000271697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006729211,"about_ca_system_score_gemma":0.0007080596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007678908,"about_ca_topic_score_gemma":0.0009276192,"domain_scores_codex":[0.999647,0.00004749116,0.00002191529,0.00008693484,0.0001753739,0.0000212053],"domain_scores_gemma":[0.999808,0.0000747423,0.00005177663,0.0000146774,0.00003701001,0.00001383729],"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":[0.00002182485,0.00001493479,0.0001114898,0.00004332164,0.000003855924,0.00002241876,0.00001832347,0.00007838524,0.9954591,0.0003275843,0.0001745741,0.003724233],"study_design_scores_gemma":[0.00001753916,0.0001672624,0.001043729,0.00001196806,0.00001746823,0.0002749657,0.00001113628,0.003470942,0.9846523,0.0001472601,0.01016057,0.00002490545],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6369933,0.00942996,0.3373763,0.0016152,0.0008265451,0.0006037701,0.001382473,0.002574438,0.009198022],"genre_scores_gemma":[0.6462119,0.002737622,0.3421737,0.0008570566,0.0001800711,0.0006421127,0.0004280527,0.00003952655,0.006729941],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008081544,"threshold_uncertainty_score":0.004882395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0129326752461881,"score_gpt":0.2435735962702553,"score_spread":0.2306409210240672,"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."}}