{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003456712,0.0001044929,0.0001009968,0.00002183095,0.00005546745,0.0000251655,0.00004964956,0.0001075644,0.00002710188],"category_scores_gemma":[0.0000696561,0.0001064066,0.00005973529,0.0001554427,0.00001171492,0.00007039626,0.000005386831,0.0001076305,0.00005491348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000349518,"about_ca_system_score_gemma":0.000003936249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008815673,"about_ca_topic_score_gemma":0.000009437807,"domain_scores_codex":[0.9994423,0.000008490197,0.0001428969,0.0001680933,0.00006386857,0.0001743851],"domain_scores_gemma":[0.9997453,0.00002016259,0.00002108195,0.00006661215,0.00003444268,0.0001124007],"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":[0.00001860347,0.000006127398,0.000001129868,0.00004048064,0.00001093538,3.737518e-7,0.00003435394,0.0005289992,0.964726,0.000008394873,0.0004722175,0.03415235],"study_design_scores_gemma":[0.0001826523,0.00007905385,0.00003890098,0.000006513789,0.00001225169,0.000001216172,0.00001163306,0.1751112,0.8163567,0.00003612684,0.008049742,0.0001140313],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5789137,0.0001097341,0.4184209,0.0003532343,0.000564363,0.0002937396,0.00002114289,0.0007229772,0.0006001883],"genre_scores_gemma":[0.9989315,0.0000314555,0.0006536959,0.00009931719,0.0001401815,0.00001669402,0.00001091728,0.00002405171,0.00009222642],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4200177,"threshold_uncertainty_score":0.4339136,"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."}}