{"id":"W4412780604","doi":"10.3389/fsci.2025.1575468","title":"Harnessing agri-food system microbiomes for sustainability and human health","year":2025,"lang":"en","type":"article","venue":"Frontiers in Science","topic":"Probiotics and Fermented Foods","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Microbiome; Sustainability; Food systems; Human health; Environmental resource management; Business; Environmental planning; Geography; Food security; Biology; Environmental health; Environmental science; Ecology; Medicine; Agriculture; Bioinformatics","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":[],"consensus_categories":[],"category_scores_codex":[0.0009536767,0.00008080958,0.0001624327,0.00005661104,0.000649734,0.0001354728,0.0002899031,0.00004013314,6.322319e-7],"category_scores_gemma":[0.00005004518,0.00003515034,0.00002765409,0.0008290187,0.0004064083,0.0001247224,0.0001079717,0.00005886191,8.11275e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000299746,"about_ca_system_score_gemma":0.00008306399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009884685,"about_ca_topic_score_gemma":0.0001013714,"domain_scores_codex":[0.9989764,0.00003000422,0.0001874133,0.0003642442,0.00008580679,0.0003561396],"domain_scores_gemma":[0.9997126,0.00002618511,0.00005811981,0.00005739187,0.00008063346,0.00006500301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00007492644,0.0003472917,0.3136736,0.001056182,0.00002514805,0.000002049448,0.0008982975,0.00001429495,0.2038777,0.09299635,0.004672351,0.3823618],"study_design_scores_gemma":[0.0008023921,0.0009973149,0.9280953,0.0004556069,0.00001183664,0.000004519443,0.01784521,0.00190992,0.007368507,0.02836996,0.01365031,0.0004891453],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939386,0.0007568118,0.001090673,0.002672562,0.000499225,0.0005581594,0.00002698257,0.00003806561,0.0004189051],"genre_scores_gemma":[0.9981679,0.000006211181,0.001551727,0.0001270319,0.00001769982,0.00001399522,0.000004815105,3.049637e-7,0.0001103594],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6144217,"threshold_uncertainty_score":0.4997295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01142176954464579,"score_gpt":0.2625370423096721,"score_spread":0.2511152727650263,"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."}}