{"id":"W4283259800","doi":"10.1021/acsomega.2c02985","title":"Metal-Enhanced Hg<sup>2+</sup>-Responsive Fluorescent Nanoprobes: From Morphological Design to Application to Natural Waters","year":2022,"lang":"en","type":"article","venue":"ACS Omega","topic":"Molecular Sensors and Ion Detection","field":"Chemistry","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; Canada First Research Excellence Fund","keywords":"Fluorescence; Fluorophore; Nanoprobe; Photobleaching; Detection limit; Materials science; Nanotechnology; Metal; Metal ions in aqueous solution; Photochemistry; Chemistry; Analytical Chemistry (journal); Nanoparticle; Environmental chemistry; Optics; Chromatography; Organic chemistry","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":[0.0002097492,0.0003459657,0.0001642612,0.0001371095,0.0001372645,0.0002744787,0.0003991882,0.0004690715,0.0004965357],"category_scores_gemma":[0.0002902021,0.0002321649,0.0001172642,0.00008498891,0.0003397966,0.0003522557,0.0002026298,0.0002421899,0.0004485612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003021317,"about_ca_system_score_gemma":0.0001424718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004645891,"about_ca_topic_score_gemma":0.001108608,"domain_scores_codex":[0.9999107,0.00001175829,0.000006194447,0.00003385976,0.00002191578,0.00001558431],"domain_scores_gemma":[0.9998533,0.00003454714,0.00003840452,0.00001536785,0.00003885381,0.00001955769],"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":[0.00001140014,0.000002756762,0.00005594109,0.0000265192,0.000002178004,0.00001925627,0.000009794939,0.0000761585,0.9981049,0.0001227454,0.00003584299,0.001532408],"study_design_scores_gemma":[0.000001481482,0.00002497066,0.0003848269,0.000001382279,0.000002557464,0.00009808815,0.000006964388,0.000819767,0.9976614,0.0000284193,0.0009674963,0.00000273824],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7826372,0.003276401,0.2069078,0.0004932823,0.0000856183,0.0002129777,0.000671317,0.001962584,0.003752817],"genre_scores_gemma":[0.8168174,0.001351576,0.176222,0.000254876,0.00001606161,0.0001079702,0.0002946649,0.0001323907,0.00480292],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004965357,"threshold_uncertainty_score":0.00219214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01079879744314007,"score_gpt":0.2252069895686684,"score_spread":0.2144081921255284,"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."}}