{"id":"W3094120268","doi":"10.1002/smll.202004162","title":"Encapsulated Nanodroplets for Enhanced Fluorescence Detection by Nano‐Extraction","year":2020,"lang":"en","type":"article","venue":"Small","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Fluorophore; Fluorescence; Nanotechnology; Materials science; Microscopy; Fluorescence microscope; Chemical imaging; Extraction (chemistry); Chemistry; Chromatography; Optics; Hyperspectral imaging; Computer 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":[0.0002385433,0.0004543824,0.0003654248,0.0002124654,0.0001306183,0.0003407338,0.0005173943,0.0005558766,0.0006400155],"category_scores_gemma":[0.0003141392,0.0003170306,0.0003248001,0.0001625934,0.000210788,0.0004536929,0.0004194635,0.0006742271,0.0006822385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003924941,"about_ca_system_score_gemma":0.000213099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002902682,"about_ca_topic_score_gemma":0.0005067601,"domain_scores_codex":[0.9998204,0.00002272793,0.00001672181,0.00004208587,0.00007885211,0.00001921287],"domain_scores_gemma":[0.9998491,0.00004189182,0.00003640805,0.00002232931,0.00003392322,0.0000163946],"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":[0.00000782952,0.000007577248,0.00001425751,0.0000235228,0.000002647494,0.00001354847,0.000006962165,0.0001044126,0.998145,0.0001152556,0.00003082328,0.001528297],"study_design_scores_gemma":[0.000004013622,0.0000337136,0.00007323388,0.000001760716,0.000003480052,0.00002567101,0.000001317932,0.001233681,0.9974599,0.00002360692,0.001135502,0.000003987317],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7480434,0.005099084,0.2400642,0.0003903784,0.0002283254,0.0003986687,0.0007194973,0.001188996,0.003867578],"genre_scores_gemma":[0.8291469,0.002582284,0.160489,0.0002798192,0.00005028175,0.0002996078,0.000741145,0.0002430587,0.006167798],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006400155,"threshold_uncertainty_score":0.002847791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01156327115003669,"score_gpt":0.1999322963213212,"score_spread":0.1883690251712845,"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."}}