{"id":"W4317892516","doi":"10.1021/acssensors.2c01730","title":"Biosensor Optimization Using a Förster Resonance Energy Transfer Pair Based on mScarlet Red Fluorescent Protein and an mScarlet-Derived Green Fluorescent Protein","year":2023,"lang":"en","type":"article","venue":"ACS Sensors","topic":"Transgenic Plants and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Innovates - Technology Futures; University of Alberta; Uehara Memorial Foundation","keywords":"Förster resonance energy transfer; Biosensor; Fluorescence; Autofluorescence; Green fluorescent protein; Fluorescent protein; Protein engineering; Chemistry; Yellow fluorescent protein; Biophysics; Aequorea victoria; Cyan; Biochemistry; Biology; Enzyme","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":[0.0001279282,0.0002747068,0.0001949273,0.0001007647,0.0002386264,0.00003792251,0.0001568242,0.0002185687,0.000009253345],"category_scores_gemma":[0.00001610813,0.0002565806,0.00007517905,0.0002342735,0.00009576148,0.000010515,0.00003993269,0.0001005953,0.000003373244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002278114,"about_ca_system_score_gemma":0.00005502915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001101184,"about_ca_topic_score_gemma":0.00006349452,"domain_scores_codex":[0.9983346,0.000142023,0.0002729252,0.0006496715,0.0002165945,0.0003842112],"domain_scores_gemma":[0.9992368,0.000009493634,0.00004826113,0.0004845955,0.00006901837,0.0001518283],"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":[0.0002580677,0.00009548364,0.0001111265,0.00002743803,0.00002291674,0.00001272587,0.00007519968,0.007813556,0.990025,0.00006006562,0.0001087404,0.001389705],"study_design_scores_gemma":[0.001138736,0.0002953448,0.001107325,0.00009556399,0.0000230129,0.000007304717,0.00004488015,0.06961245,0.9191816,0.00001120632,0.008083328,0.000399232],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938563,0.00007147456,0.00395604,0.0009668485,0.00002810615,0.0008053344,0.0001872082,0.00009124143,0.00003744811],"genre_scores_gemma":[0.9957812,0.00007104074,0.002799371,0.0002609744,0.0001482838,0.000134578,0.0004972156,0.00006597962,0.0002414026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07084335,"threshold_uncertainty_score":0.9999886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01782693448740932,"score_gpt":0.2397017933888294,"score_spread":0.22187485890142,"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."}}