{"id":"W4410975458","doi":"10.3389/frmbi.2025.1602938","title":"Editorial: Harnessing machine learning to decode plant-microbiome dynamics for sustainable agriculture","year":2025,"lang":"en","type":"editorial","venue":"Frontiers in Microbiomes","topic":"Agricultural Development and Management","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Microbiome; Agriculture; Sustainable agriculture; Computer science; Dynamics (music); Biology; Ecology; Bioinformatics; Sociology","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":[0.005408541,0.003851276,0.003877853,0.00303839,0.002679576,0.007739602,0.004575788,0.01458357,0.02825548],"category_scores_gemma":[0.01719846,0.001328496,0.003346981,0.001391927,0.002640069,0.005332575,0.001720859,0.01726092,0.01823455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002537128,"about_ca_system_score_gemma":0.002146512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001322628,"about_ca_topic_score_gemma":0.002327942,"domain_scores_codex":[0.9968343,0.000364423,0.0003555608,0.0006404546,0.001514455,0.0002907014],"domain_scores_gemma":[0.9819254,0.00774469,0.0009730344,0.0005392753,0.006306571,0.002511044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001116256,0.00002494635,0.00005755578,0.0003319987,0.00003049467,0.0000864195,0.00001458417,0.00008681236,0.0001977764,0.0006257853,0.9902322,0.008199656],"study_design_scores_gemma":[0.0001165361,0.00008656689,0.000481004,0.0003942052,0.00007631027,0.0002296479,0.00003767199,0.0005261287,0.0003724977,0.00234447,0.9952945,0.00004038339],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0001053513,0.005177315,0.0004647005,0.03109985,0.9611966,0.00002921737,0.0002445028,0.0002145604,0.001467923],"genre_scores_gemma":[0.000702192,0.004247606,0.0002664555,0.01864831,0.9673674,0.00003700082,0.0001091008,0.00008828936,0.008533665],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.02825548,"threshold_uncertainty_score":0.09452403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003027449354206813,"score_gpt":0.1948839730190761,"score_spread":0.1918565236648693,"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."}}