{"id":"W4403923059","doi":"10.1021/acsanm.4c05274","title":"Dispersive Liquid–Liquid Microextraction (DLLME) Coupled with Droplet Evaporation on an Omniphobic Nano/Micro Structured Porous Microfiber Membrane for Surface-Enhanced Raman Spectroscopy","year":2024,"lang":"en","type":"article","venue":"ACS Applied Nano Materials","topic":"Gold and Silver Nanoparticles Synthesis and Applications","field":"Materials Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates","keywords":"Microfiber; Materials science; Evaporation; Raman spectroscopy; Membrane; Nano-; Porosity; Nanotechnology; Chemical engineering; Chemistry; Composite material; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005667154,0.0005103156,0.0006136672,0.0001124164,0.0004563789,0.0007469211,0.0003600317,0.0002305526,0.0007424883],"category_scores_gemma":[0.00001175584,0.000403892,0.00007591517,0.0002841243,0.0001495786,0.0003776661,0.00004821465,0.0000981858,0.0002955434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001759965,"about_ca_system_score_gemma":0.0001553882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007879479,"about_ca_topic_score_gemma":0.00004557623,"domain_scores_codex":[0.9971104,0.00009253623,0.0006865552,0.001084748,0.0003481953,0.0006775584],"domain_scores_gemma":[0.9986109,0.0001437015,0.0003058272,0.0006456133,0.0001346206,0.0001593091],"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":[0.003529774,0.0001733613,4.731014e-7,0.0001293077,0.00004185445,0.000004335357,0.0004664685,0.0001708132,0.9919673,0.003076621,0.0003778024,0.00006184938],"study_design_scores_gemma":[0.0009347748,0.0008781181,0.00001611265,0.00009285082,0.0001448217,0.00001596162,0.0002354966,0.00001594338,0.9958817,0.0002201269,0.001016685,0.0005473565],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995267,0.00008985626,0.0005848615,0.0003475088,0.0007282976,0.002000457,0.000546193,0.0003389973,0.00009682661],"genre_scores_gemma":[0.995613,0.00007335688,0.002455104,0.0002284754,0.0003992796,0.0004339177,0.0004899031,0.0001188017,0.0001881315],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003914412,"threshold_uncertainty_score":0.9998413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009702018306238585,"score_gpt":0.248107009279093,"score_spread":0.2384049909728544,"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."}}