{"id":"W3046158368","doi":"10.1101/2020.07.30.229633","title":"Genetically-encoded fluorescent biosensor for rapid detection of protein expression","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Viral Infectious Diseases and Gene Expression in Insects","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Searle Scholars Program; Hellman Foundation; Burroughs Wellcome Fund; National Institutes of Health; National Science Foundation","keywords":"Fluorescent protein; Biosensor; Fluorescence; Protein expression; Computational biology; Green fluorescent protein; Chemistry; Biology; Molecular biology; Cell biology; Genetics; Gene; Biochemistry; Physics","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":[0.0002876798,0.000325891,0.0002618413,0.0002405121,0.0001156653,0.0003224472,0.0004911291,0.0008261029,0.001024851],"category_scores_gemma":[0.0003781792,0.0002383678,0.000206565,0.0002134585,0.0002632971,0.0003246295,0.0002857015,0.0009284153,0.0006477531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004539579,"about_ca_system_score_gemma":0.000253393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003439173,"about_ca_topic_score_gemma":0.0003876864,"domain_scores_codex":[0.9997371,0.00003521107,0.00001573985,0.00006320493,0.0001220292,0.00002670065],"domain_scores_gemma":[0.9998522,0.0000533755,0.00002515022,0.00001730093,0.00003003323,0.00002191274],"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":[0.000007387026,0.000005379344,0.0000389771,0.00001514643,0.000001289431,0.000007757241,0.000003402087,0.00007182358,0.9988869,0.0001595614,0.0000769748,0.0007254626],"study_design_scores_gemma":[0.000005609304,0.0000420268,0.000300428,0.000002799675,0.000003071995,0.00007150697,0.000004742411,0.002626584,0.9948613,0.00007542571,0.002000419,0.000005982981],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5967605,0.003155258,0.3911786,0.0007070399,0.0003024738,0.0001910433,0.001325338,0.002487368,0.003892341],"genre_scores_gemma":[0.7765529,0.001611957,0.2144809,0.0002553122,0.00004402961,0.0001995916,0.001020439,0.0001168712,0.00571799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001024851,"threshold_uncertainty_score":0.003428459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01311427605606449,"score_gpt":0.2301296361947207,"score_spread":0.2170153601386562,"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."}}