{"id":"W3116538249","doi":"10.3389/fevo.2020.605304","title":"Host-Specificity and Core Taxa of Seagrass Leaf Microbiome Identified Across Tissue Age and Geographical Regions","year":2020,"lang":"en","type":"article","venue":"Frontiers in Ecology and Evolution","topic":"Marine and coastal plant biology","field":"Earth and Planetary Sciences","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Tula Foundation; University of British Columbia","funders":"Hakai Institute; Natural Sciences and Engineering Research Council of Canada; Mitacs; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Tula Foundation","keywords":"Seagrass; Zostera marina; Epiphyte; Biology; Microbiome; Ecology; Trophic level; Ecosystem; Microbial population biology; Metagenomics; Bacteria","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0001840631,0.0001848025,0.0002259257,0.0006434859,0.0003516583,0.000597287,0.0001863824,0.0002212556,0.0008809625],"category_scores_gemma":[0.0006488991,0.0001376132,0.0001741422,0.000558952,0.0003047489,0.00027078,0.0006629776,0.0001789904,0.0001585261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005336445,"about_ca_system_score_gemma":0.0004289117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1083703,"about_ca_topic_score_gemma":0.2911895,"domain_scores_codex":[0.9997806,0.0000154581,0.00001340257,0.00009080439,0.00003527299,0.00006457776],"domain_scores_gemma":[0.9995019,0.00004061363,0.0001448196,0.0000316593,0.0001754526,0.0001054885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001464556,0.000007632168,0.9492063,0.00003798253,0.00005334165,0.00004990924,0.000984174,0.00008088787,0.04319561,0.00003547817,0.0001518538,0.006050329],"study_design_scores_gemma":[4.802347e-7,0.00001049681,0.9992989,0.000003034321,0.000005181058,0.00002402075,0.0003139038,0.00003696337,0.0001777816,0.000005707764,0.0001219944,0.000001484368],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989188,0.0001618402,0.0001122247,0.000009443903,0.000001413194,0.000003194427,0.0005182974,0.000003925827,0.0002709436],"genre_scores_gemma":[0.998467,0.0001230107,0.0002558062,0.00002561459,0.000001477489,0.000008035375,0.0007172307,0.000004458652,0.0003973701],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1083703,"threshold_uncertainty_score":0.2154789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01412957733708337,"score_gpt":0.2123990019687319,"score_spread":0.1982694246316485,"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."}}