{"id":"W4226323283","doi":"10.1186/s40168-022-01234-x","title":"The phyllosphere microbiome shifts toward combating melanose pathogen","year":2022,"lang":"en","type":"article","venue":"Microbiome","topic":"Plant-Microbe Interactions and Immunity","field":"Agricultural and Biological Sciences","cited_by":238,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"National Key Research and Development Program of China; Earmarked Fund for China Agriculture Research System; Zhejiang University","keywords":"Phyllosphere; Biology; Microbiome; Microbial ecology; Methylobacterium; Microbiology; Metagenomics; Sphingomonas; Human pathogen; Bacteria; Pseudomonas; Genetics; Gene","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":[0.0002625257,0.0004724636,0.0002756329,0.0004600848,0.0003020257,0.0007376654,0.000194356,0.0005462694,0.0008262694],"category_scores_gemma":[0.0002503934,0.0001707013,0.0003676854,0.0002741675,0.0003347965,0.0005453452,0.0007323994,0.0005199591,0.000239749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002743995,"about_ca_system_score_gemma":0.0002815373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007157513,"about_ca_topic_score_gemma":0.0007045312,"domain_scores_codex":[0.9997526,0.00002736154,0.00001376015,0.0001028631,0.0000531088,0.00005039224],"domain_scores_gemma":[0.9998161,0.00002548277,0.00006246982,0.00001670253,0.00003558663,0.00004360822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001527105,0.00002814183,0.01325463,0.000161824,0.0000285338,0.00008499312,0.0001803622,0.000196709,0.9802852,0.0001057917,0.0001032196,0.005417847],"study_design_scores_gemma":[0.00002598035,0.0006441236,0.57194,0.0001732644,0.0001623894,0.001055242,0.001622754,0.004955308,0.405982,0.0008289941,0.01254576,0.00006415712],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931141,0.001581606,0.002684507,0.0001354384,0.00001766763,0.00004168677,0.001111809,0.00008913904,0.001224048],"genre_scores_gemma":[0.9920787,0.0009478173,0.004390959,0.0002661881,0.00001227784,0.0000742647,0.001348881,0.00002793859,0.0008529217],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008262694,"threshold_uncertainty_score":0.002764165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01621986440806735,"score_gpt":0.2071094417975165,"score_spread":0.1908895773894491,"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."}}