{"id":"W4390706802","doi":"10.1111/1462-2920.16582","title":"Manipulation of the seagrass‐associated microbiome reduces disease severity","year":2024,"lang":"en","type":"article","venue":"Environmental Microbiology","topic":"Marine and coastal plant biology","field":"Earth and Planetary Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Hakai Institute; Division of Ocean Sciences; University of British Columbia; University of Washington; Fisheries and Oceans Canada; Tula Foundation; Institut Nordique De Recherche En Environnement Et En Santé Au Travail; Cornell University; National Science Foundation","keywords":"Biology; Microbiome; Zostera marina; Seagrass; Disease; Metagenomics; Ecology; Ecosystem; Bioinformatics; Genetics; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001405279,0.0003206567,0.0002418754,0.0001551673,0.0001711528,0.0004802227,0.000175787,0.000269237,0.001259097],"category_scores_gemma":[0.0001850912,0.0001225465,0.0001556775,0.000102119,0.0002379817,0.0002088048,0.0003353156,0.0005355181,0.0001419592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000336053,"about_ca_system_score_gemma":0.0002777883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002145759,"about_ca_topic_score_gemma":0.004437401,"domain_scores_codex":[0.9998425,0.00002470157,0.00001091346,0.00004535284,0.0000300149,0.00004644557],"domain_scores_gemma":[0.9997473,0.00003170009,0.00006469687,0.00002247912,0.0000261978,0.0001075274],"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":[0.0001199872,0.00002914908,0.0005213509,0.00001733431,0.000005551094,0.000004185697,0.00001616913,0.00002160906,0.9985642,0.00001163719,0.00001042681,0.0006784299],"study_design_scores_gemma":[0.00007955297,0.004451844,0.1781496,0.00003036424,0.0001089447,0.00009674318,0.0004676881,0.002759757,0.8097471,0.000161074,0.003922668,0.00002476206],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984084,0.0001756223,0.0007244397,0.00004520696,0.00001508395,0.00001479928,0.0001523806,0.00005063857,0.0004134744],"genre_scores_gemma":[0.9973457,0.0001475102,0.001068469,0.00009885796,0.000003387863,0.00002488109,0.0002440361,0.00001623329,0.001051037],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002145759,"threshold_uncertainty_score":0.00426656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006094791449914303,"score_gpt":0.1687122428666314,"score_spread":0.162617451416717,"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."}}