{"id":"W3045917282","doi":"10.1021/acssensors.9b02490","title":"Sensitive Detection of Broad-Spectrum Bacteria with Small-Molecule Fluorescent Excimer Chemosensors","year":2020,"lang":"en","type":"article","venue":"ACS Sensors","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Connaught Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation; Ontario Research Foundation","keywords":"Fluorescence; Flow cytometry; Bacteria; Broad spectrum; Biophysics; Chemistry; Nanotechnology; Biology; Combinatorial chemistry; Materials science; Molecular biology","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":[0.00004583469,0.0002511093,0.0003063571,0.00007031328,0.00004933368,0.00002503419,0.00007216653,0.0001361782,0.000028607],"category_scores_gemma":[0.0000305649,0.000224273,0.00009226018,0.0004050625,0.00008086358,0.00006829474,0.0000222161,0.0002556246,0.00009161021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004762007,"about_ca_system_score_gemma":0.000008419563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003634441,"about_ca_topic_score_gemma":0.00002391258,"domain_scores_codex":[0.9988978,0.00003779132,0.000269579,0.0002896814,0.0001871798,0.0003179943],"domain_scores_gemma":[0.9994773,0.00003250966,0.00005883588,0.0001878855,0.00006772875,0.0001757873],"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":[0.0001287314,0.00001966411,0.00004170531,0.00007885455,0.0001166916,0.00003489685,0.0003191504,0.003278545,0.9943601,0.00002437513,0.00005573962,0.001541553],"study_design_scores_gemma":[0.0003819164,0.0002124649,0.002144105,0.00003075967,0.00006141119,0.00002705386,0.0001877285,0.02776717,0.9682862,0.000006381306,0.0006170294,0.0002777416],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954574,0.00002772625,0.002818379,0.0003402924,0.0001109913,0.0001688211,0.00001405569,0.0003016584,0.0007607068],"genre_scores_gemma":[0.9991525,0.0000449635,0.0004191095,0.0001044774,0.0001554344,0.000002744182,0.000007228199,0.00006288569,0.00005064862],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02607385,"threshold_uncertainty_score":0.9145586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01012297317024593,"score_gpt":0.1777814175216452,"score_spread":0.1676584443513993,"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."}}