{"id":"W4399665209","doi":"10.1021/acssynbio.3c00736","title":"Design and Characterization of a Generalist Biosensor for Indole Derivatives","year":2024,"lang":"en","type":"article","venue":"ACS Synthetic Biology","topic":"Analytical Chemistry and Chromatography","field":"Chemistry","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Government of Ontario; Genome Canada","keywords":"Generalist and specialist species; Indole test; Biosensor; Characterization (materials science); Computational biology; Chemistry; Combinatorial chemistry; Biochemistry; Biochemical engineering; Biology; Nanotechnology; Ecology; Engineering; 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":[0.00006167995,0.00009235296,0.0001507434,0.00002953351,0.00003043414,0.0000120311,0.00006564841,0.0001384711,0.0001081975],"category_scores_gemma":[0.00003726969,0.00007570701,0.00004478774,0.00006942399,0.0002918907,0.000022337,0.00002162359,0.00004785341,0.000002209903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005066559,"about_ca_system_score_gemma":0.00001603837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001366267,"about_ca_topic_score_gemma":5.783133e-8,"domain_scores_codex":[0.9994795,0.0000151719,0.0001548238,0.0002039974,0.00002472228,0.0001218032],"domain_scores_gemma":[0.9996023,0.0002060563,0.00003838113,0.00009639496,0.00002553497,0.00003129627],"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":[0.00002075038,0.00001857742,0.0001506337,0.0002795976,0.00005852022,8.150678e-7,0.0000617002,3.178273e-7,0.9932298,0.004430855,0.00001583853,0.001732616],"study_design_scores_gemma":[0.0001006144,0.00002809287,0.00003468484,0.00005857988,0.00003808303,0.0000117207,0.00002256535,0.0009825859,0.9934033,0.002131999,0.003098147,0.00008960866],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.963218,0.0003236014,0.03552177,0.0002835414,0.00003063126,0.00005992973,0.00008140552,0.000050413,0.0004306464],"genre_scores_gemma":[0.9983851,0.00008282809,0.001140811,0.00002985875,0.00005537858,0.00002589683,0.00007155781,0.00001104634,0.0001975168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03516704,"threshold_uncertainty_score":0.3087242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02048214522096301,"score_gpt":0.2573655806339932,"score_spread":0.2368834354130302,"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."}}