{"id":"W4293817200","doi":"10.1049/enb2.12024","title":"A curcumin direct protein biosensor for cell‐free prototyping","year":2022,"lang":"en","type":"article","venue":"Engineering Biology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kensington Health","funders":"Engineering and Physical Sciences Research Council","keywords":"Biosensor; Synthetic biology; Curcumin; Fluorescence; Substrate (aquarium); Protein engineering; Green fluorescent protein; Cell-free protein synthesis; Chemistry; Combinatorial chemistry; Escherichia coli; Biochemistry; Cofactor; Cell-free system; Directed evolution; Nanotechnology; Enzyme; Computational biology; Biology; Protein biosynthesis; Materials science; Gene","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003936519,0.0006027484,0.0003685174,0.0002777231,0.0002084259,0.000437069,0.0009338426,0.0007707158,0.00327104],"category_scores_gemma":[0.0004151996,0.0003455298,0.0003415022,0.0001776901,0.0003138928,0.0005369216,0.0005816726,0.0007582129,0.002133674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006344782,"about_ca_system_score_gemma":0.0003176493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005389274,"about_ca_topic_score_gemma":0.0008458836,"domain_scores_codex":[0.9993538,0.00006912141,0.0000299307,0.0001737102,0.0003228667,0.00005063801],"domain_scores_gemma":[0.9997205,0.00008054596,0.00005432245,0.00004051507,0.00007136452,0.00003265288],"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":[0.000007219412,0.000008390893,0.00001961115,0.00002507852,0.000001343149,0.00001634509,0.000006518359,0.00004807581,0.9986091,0.0001159807,0.00009753971,0.001044737],"study_design_scores_gemma":[0.00000382256,0.00003762815,0.00009073864,0.000002348758,0.000002288944,0.00004489858,0.000005895256,0.001026417,0.9959288,0.00002403766,0.00282797,0.000005184111],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5487682,0.002414144,0.4272544,0.001075304,0.0006604764,0.0004422539,0.001220325,0.004467844,0.01369711],"genre_scores_gemma":[0.7382506,0.001365271,0.229895,0.0002843838,0.00006355298,0.0005245212,0.0007955909,0.0003824719,0.02843864],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00327104,"threshold_uncertainty_score":0.01094276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005680150741722711,"score_gpt":0.2730709440880348,"score_spread":0.2673907933463121,"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."}}