{"id":"W2967903246","doi":"10.1021/acsami.9b10996","title":"Ratiometric Detection of Nerve Agents by Coupling Complementary Properties of Silicon-Based Quantum Dots and Green Fluorescent Protein","year":2019,"lang":"en","type":"article","venue":"ACS Applied Materials & Interfaces","topic":"Carbon and Quantum Dots Applications","field":"Materials Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; University of the Philippines; China Scholarship Council; University of Alberta; Government of Canada","keywords":"Paraoxon; Photoluminescence; Fluorescence; Materials science; Quantum dot; Quenching (fluorescence); Multiplex; Nanotechnology; Detection limit; PMOS logic; Silicon; Combinatorial chemistry; Photochemistry; Optoelectronics; Chemistry; Chromatography; Organic chemistry; Bioinformatics; Transistor","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":[0.0004367259,0.0002101389,0.0004417232,0.0001835479,0.00006792947,0.00007570159,0.0002545684,0.00007292293,0.0004036404],"category_scores_gemma":[0.00001275968,0.0001769332,0.00001708964,0.000223691,0.0001610047,0.000103048,0.0001440052,0.00005064807,0.00003415093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003857089,"about_ca_system_score_gemma":0.00003008281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00163741,"about_ca_topic_score_gemma":0.00002996142,"domain_scores_codex":[0.9983698,0.00003991219,0.0006870925,0.0003752819,0.0002968419,0.0002311271],"domain_scores_gemma":[0.999029,0.00003636026,0.0004663827,0.0003314589,0.00009128652,0.00004548372],"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":[0.0002768555,0.0001128956,0.0000622205,0.0004836167,0.00001814851,1.225661e-7,0.0001624109,0.00005026626,0.9982312,0.0003529483,0.00002101741,0.0002282646],"study_design_scores_gemma":[0.0007035466,0.000173007,0.0002348494,0.0001070078,0.00002785592,7.065715e-7,0.000262693,0.0002697998,0.9979016,0.0001016067,0.00003394091,0.0001833488],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977428,0.0002234665,0.00004859807,0.00006420251,0.0001677127,0.001465674,0.0002135702,0.00004991167,0.00002407355],"genre_scores_gemma":[0.9995992,0.00001194454,0.00006723795,0.00002965201,0.00002189725,0.0001921504,0.00003244438,0.00002570607,0.00001978327],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001856393,"threshold_uncertainty_score":0.7215128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02053810153918796,"score_gpt":0.2378508514714767,"score_spread":0.2173127499322887,"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."}}