{"id":"W3160863507","doi":"10.1016/j.bioactmat.2021.04.022","title":"Multiplexed detection and differentiation of bacterial enzymes and bacteria by color-encoded sensor hydrogels","year":2021,"lang":"en","type":"article","venue":"Bioactive Materials","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Infection and Immunity","funders":"H2020 European Research Council; Ministère de l’Europe et des Affaires étrangères; Bundesministerium für Bildung und Frauen; Ministère de l'Europe et des Affaires Étrangères; Bundesministerium für Bildung und Forschung; Deutscher Akademischer Austauschdienst; Max-Buchner-Forschungsstiftung; European Research Council; Ministère de l'Enseignement supérieur, de la Recherche et de l'Innovation","keywords":"Self-healing hydrogels; Bacteria; Enzyme; Staphylococcus aureus; Escherichia coli; Strain (injury); Chemistry; Microbiology; Biochemistry; Biology; Gene; Polymer chemistry","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":[0.0002829018,0.0005421059,0.000252878,0.0003086022,0.00007038852,0.0003273442,0.0004363165,0.0003563377,0.0004719066],"category_scores_gemma":[0.0003921177,0.0002109725,0.00022366,0.000205073,0.0002186094,0.0003719403,0.0003117571,0.0003776599,0.0001912077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002865815,"about_ca_system_score_gemma":0.000138107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000244871,"about_ca_topic_score_gemma":0.000620336,"domain_scores_codex":[0.9996618,0.0000430141,0.00002238312,0.00009888645,0.0001259249,0.00004794608],"domain_scores_gemma":[0.9997172,0.00009178451,0.00008676857,0.00002359201,0.00004987597,0.00003072995],"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":[0.00001707117,0.000008538659,0.00006782848,0.00001759469,0.000002509775,0.00002087009,0.000007069325,0.00009526295,0.9984797,0.00003690852,0.00001356822,0.001233265],"study_design_scores_gemma":[0.000002880064,0.00003417007,0.0002465723,0.000001754216,0.000004449251,0.0000400752,0.000004292482,0.001315335,0.998085,0.00001485561,0.0002461101,0.000004614362],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9315206,0.002571276,0.0632012,0.0001252556,0.000092487,0.0001306972,0.0004359809,0.000317957,0.001604551],"genre_scores_gemma":[0.9035999,0.001450376,0.09132707,0.0001324079,0.00003923993,0.0001723712,0.0003038927,0.00004201375,0.002932811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005421059,"threshold_uncertainty_score":0.002079308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007441762287408023,"score_gpt":0.192892990389011,"score_spread":0.1854512281016029,"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."}}