{"id":"W4387409199","doi":"10.1016/j.matt.2023.09.007","title":"A bacterially engineered macrophage sponge as a neutralization decoy to treat bacterial infection","year":2023,"lang":"en","type":"article","venue":"Matter","topic":"Immune Response and Inflammation","field":"Immunology and Microbiology","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Fundo para o Desenvolvimento das Ciências e da Tecnologia; Science and Technology Development Fund; Science, Technology and Innovation Commission of Shenzhen Municipality; Universidade de Macau; National Natural Science Foundation of China","keywords":"Neutralization; Bacteria; Microbiology; Biology; Pathogen; Decoy; Immune system; Biofilm; Macrophage; Bacterial cell structure; Antibody; Receptor; Cell biology; Immunology; In vitro; Biochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001625727,0.0001458344,0.0001598017,0.0002640087,0.0001015328,0.00005115921,0.00007928893,0.0001841603,0.00770592],"category_scores_gemma":[0.00004363449,0.0001385362,0.00006264744,0.0002722433,0.00001791474,0.0001610802,0.0000513074,0.0000813596,0.05154335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004301817,"about_ca_system_score_gemma":0.00002420133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001388056,"about_ca_topic_score_gemma":0.00001385261,"domain_scores_codex":[0.999106,0.0001555655,0.000232203,0.0001966734,0.00002607427,0.0002834716],"domain_scores_gemma":[0.9996547,0.00003957989,0.00004602497,0.000201388,0.00003776744,0.00002057505],"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":[0.0005309168,0.00001878204,0.0006356183,0.00001895909,0.00002576505,0.000008323597,0.0004912484,0.00002306022,0.9733221,0.00004985798,0.02300144,0.001873931],"study_design_scores_gemma":[0.00106802,0.0001617878,0.1764289,0.0000258634,0.0000269169,0.00005830585,0.00001479358,0.000005461318,0.647787,0.00003207385,0.1741814,0.000209432],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957228,0.00001239019,0.000180572,0.0008443004,0.001607513,0.0002864655,0.00001299064,0.0002197059,0.001113283],"genre_scores_gemma":[0.9811425,0.0000175427,0.00001625604,0.0004594769,0.0001344788,0.00007224388,0.0007553501,0.00002933265,0.01737277],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3255351,"threshold_uncertainty_score":0.9932012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007348093166815866,"score_gpt":0.2344715155369965,"score_spread":0.2271234223701807,"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."}}