{"id":"W3197785375","doi":"10.3390/biom11091276","title":"Design and Prototyping of Genetically Encoded Arsenic Biosensors Based on Transcriptional Regulator AfArsR","year":2021,"lang":"en","type":"article","venue":"Biomolecules","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Higher Education Commision, Pakistan; University of Alberta","keywords":"Biosensor; Förster resonance energy transfer; Green fluorescent protein; Chemistry; Nanotechnology; Computational biology; Biochemistry; Fluorescence; Biophysics; Biology; Gene; Materials 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":[0.0001427596,0.0001651663,0.0001759877,0.00006945603,0.00005498289,0.00001635839,0.00007736673,0.0001509128,0.000004102132],"category_scores_gemma":[0.00007283437,0.0001490673,0.0001110876,0.0001655293,0.0002488131,0.000001955521,0.00002703508,0.00005068603,6.982129e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008122273,"about_ca_system_score_gemma":0.00009615423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001518538,"about_ca_topic_score_gemma":0.00000286066,"domain_scores_codex":[0.9988871,0.0001352144,0.0002285548,0.0004110997,0.0001640159,0.0001740418],"domain_scores_gemma":[0.999388,0.00002069549,0.00007502938,0.0003008741,0.0001480292,0.00006735155],"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":[0.0001576419,0.00009265866,0.0000439119,0.00002145093,0.00004058583,0.00001028057,0.000005750286,0.00005339179,0.995369,0.0002557122,0.00005015127,0.003899481],"study_design_scores_gemma":[0.0003402212,0.0003298824,0.0004466583,0.00004937345,0.00003481638,0.00001919164,0.00001683248,0.002139271,0.9947138,0.0001504361,0.001575899,0.0001836233],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8173453,0.001389958,0.1797371,0.0007170125,0.00004142338,0.0004515196,0.00003596867,0.00005156988,0.0002301555],"genre_scores_gemma":[0.8781317,0.000174412,0.1212356,0.0002619933,0.00003771417,0.00001326722,0.00005860395,0.00001796383,0.00006880065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06078639,"threshold_uncertainty_score":0.6078789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01406740480162322,"score_gpt":0.2572567201424145,"score_spread":0.2431893153407912,"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."}}