{"id":"W4414034564","doi":"10.1016/j.scitotenv.2025.180357","title":"Soil drivers of fungal, bacterial and plant diversity in contaminated Southern Californian sites: Implications for dryland bioremediation","year":2025,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Genetics","funders":"National Institute of Food and Agriculture; U.S. Department of Agriculture; Annenberg Foundation","keywords":"Bioremediation; Environmental science; Fungal Diversity; Contamination; Ecology; Biology","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":[0.0002652359,0.000276297,0.0002630118,0.0007011674,0.0006670424,0.0008307584,0.00023946,0.0001924274,0.0006174796],"category_scores_gemma":[0.0003778504,0.0001722633,0.0001212195,0.0007741484,0.0003645197,0.0002703807,0.0003912728,0.0001989174,0.00006531124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007752721,"about_ca_system_score_gemma":0.000712464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08108921,"about_ca_topic_score_gemma":0.2162125,"domain_scores_codex":[0.9997516,0.00001971725,0.000009724309,0.0001124105,0.00005477982,0.00005166796],"domain_scores_gemma":[0.9995746,0.00004778287,0.0001710647,0.00001638716,0.0001118846,0.00007819485],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001013913,0.00003956614,0.9770114,0.00007039684,0.00004264149,0.00007636764,0.0006254708,0.0001829649,0.01519512,0.00004728701,0.00009971308,0.006507759],"study_design_scores_gemma":[0.000001546805,0.00001885028,0.9988539,0.000005111173,0.000007680518,0.00002234175,0.0006010236,0.000065892,0.0002210616,0.00001078145,0.0001900719,0.000001681838],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992908,0.0001275214,0.00005904778,0.00001488645,7.293953e-7,0.000006190595,0.0001577324,0.000002846828,0.0003402711],"genre_scores_gemma":[0.9991226,0.0001429361,0.0002162907,0.000016093,0.000002052572,0.00000604299,0.0002786513,0.000001579355,0.000213789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08108921,"threshold_uncertainty_score":0.1612344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01187162644563057,"score_gpt":0.1900984682016253,"score_spread":0.1782268417559947,"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."}}