{"id":"W3135632983","doi":"10.3389/fbioe.2021.622108","title":"Microfluidic Based Whole-Cell Biosensors for Simultaneously On-Site Monitoring of Multiple Environmental Contaminants","year":2021,"lang":"en","type":"article","venue":"Frontiers in Bioengineering and Biotechnology","topic":"bioluminescence and chemiluminescence research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Fisheries and Oceans Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Biosensor; Contamination; Environmental monitoring; Environmental science; Biochemical engineering; Microfluidics; Computer science; Nanotechnology; Engineering; Environmental engineering; Materials science; Ecology; 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":[0.00008000467,0.0001687523,0.0002197843,0.0001476892,0.00003666054,0.00000735705,0.0001336068,0.000413338,7.694837e-7],"category_scores_gemma":[0.00009391789,0.0001737157,0.00006158216,0.000139213,0.000180069,0.000003350995,0.00006656348,0.0001392819,8.215337e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002470962,"about_ca_system_score_gemma":0.00002919772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000566005,"about_ca_topic_score_gemma":0.000001541948,"domain_scores_codex":[0.9989933,0.00001320471,0.0001950989,0.0003918299,0.00007562357,0.0003309015],"domain_scores_gemma":[0.999603,0.0000276999,0.00004203394,0.000254669,0.0000225253,0.00005012195],"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":[0.00008226508,0.00009723323,0.08907622,0.00009150717,0.00001467335,0.00001483945,0.00001081893,0.00002897034,0.9066581,8.615498e-7,0.0002872965,0.003637207],"study_design_scores_gemma":[0.001026921,0.000297933,0.001381262,0.00006710023,0.000007177511,0.000009969214,0.0003483445,0.001649424,0.9869781,0.000001471905,0.008049384,0.0001828956],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9862972,0.007555908,0.005458344,0.0001948235,0.0002182418,0.0001615976,0.00009419228,0.00001637289,0.000003246182],"genre_scores_gemma":[0.9890578,0.003811123,0.006795389,0.00001959716,0.00004904149,0.00001939266,0.0001028091,0.00002147758,0.0001233289],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08769496,"threshold_uncertainty_score":0.7083921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006411347420899142,"score_gpt":0.211170273597194,"score_spread":0.2047589261762948,"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."}}