{"id":"W2912321730","doi":"10.1007/s10534-019-00179-3","title":"An engineered GFP fluorescent bacterial biosensor for detecting and quantifying silver and copper ions","year":2019,"lang":"en","type":"article","venue":"BioMetals","topic":"bioluminescence and chemiluminescence research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; University of Leeds; University of Guelph","keywords":"Biosensor; Fluorescence; Green fluorescent protein; Copper; Chemistry; Ion; Nanotechnology; Fluorescent protein; Biophysics; Materials science; Biochemistry; Biology; Gene; Physics; 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":[0.0003931361,0.0006737633,0.0004369775,0.000321799,0.000293946,0.0003867379,0.001009057,0.0007656114,0.0007373173],"category_scores_gemma":[0.0003355755,0.0002947157,0.0003452588,0.0003881482,0.0003932694,0.0003597763,0.0004299321,0.001022094,0.0006203371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001178801,"about_ca_system_score_gemma":0.0007804664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001267209,"about_ca_topic_score_gemma":0.002015777,"domain_scores_codex":[0.9996536,0.0000483952,0.00002487195,0.00007453133,0.0001450735,0.00005355818],"domain_scores_gemma":[0.9997995,0.00003478238,0.00003665751,0.00001858499,0.00005510585,0.00005527064],"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":[0.00002280625,0.00002270902,0.00005468441,0.00001990737,0.000002504109,0.00002638322,0.000006420063,0.00004083069,0.9984036,0.0002375881,0.00007028552,0.001092205],"study_design_scores_gemma":[0.000005301471,0.00003032879,0.0001979355,0.000002220935,0.000004737122,0.0001089428,0.000004521056,0.001006127,0.9973235,0.00004228268,0.001270231,0.000003830776],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7022604,0.001164937,0.2877823,0.0007567172,0.0002668836,0.0002206711,0.00179528,0.002508475,0.003244399],"genre_scores_gemma":[0.7563754,0.0007619975,0.2310948,0.0003823849,0.00002810603,0.0002497344,0.002766426,0.000248194,0.008092951],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001267209,"threshold_uncertainty_score":0.008552849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0276708473716113,"score_gpt":0.3058882936288781,"score_spread":0.2782174462572668,"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."}}