{"id":"W4404364452","doi":"10.3389/ffgc.2024.1463454","title":"Glyphosate-based herbicide contributes to nutrient variability in forest plants","year":2024,"lang":"en","type":"article","venue":"Frontiers in Forests and Global Change","topic":"Pesticide and Herbicide Environmental Studies","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of British Columbia; University of Northern British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Habitat Conservation Trust Foundation","keywords":"Glyphosate; Nutrient; Agroforestry; Agronomy; Herbicide resistance; Environmental science; Biology; Forestry; Geography; Weed control; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004006827,0.0002106299,0.0002766643,0.00006872162,0.00006302993,0.00004948264,0.0001511754,0.00009483127,0.0001398644],"category_scores_gemma":[0.0000477484,0.0001842239,0.00004071987,0.0003968972,0.00018807,0.0001568564,0.0002280111,0.0001207946,0.00005756906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008737736,"about_ca_system_score_gemma":0.000007833261,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007970296,"about_ca_topic_score_gemma":0.02061159,"domain_scores_codex":[0.9985119,0.00005399267,0.0002519923,0.0005004776,0.0002063482,0.0004752719],"domain_scores_gemma":[0.9996313,0.00005527752,0.00002177002,0.0001557243,0.000001728325,0.000134216],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000974972,0.00008232094,0.9834139,0.00003112147,0.000009273127,0.00009979574,0.0002011587,0.0002247219,0.00001736068,0.0004329786,0.006690399,0.008699514],"study_design_scores_gemma":[0.0004662682,0.00008853816,0.9601871,0.0001518398,0.000009471733,0.000002387547,0.00009467408,0.003937979,0.00004307963,0.02098088,0.01383864,0.0001991769],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98835,0.003384466,0.003726519,0.001395842,0.0006112439,0.0007233757,0.0001155047,0.00004348491,0.001649606],"genre_scores_gemma":[0.9980704,0.00007536053,0.0007980131,0.0007972879,0.00003741638,0.0001645545,0.00001654213,0.00001027319,0.00003019375],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02322679,"threshold_uncertainty_score":0.9986357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01281145960268176,"score_gpt":0.2381237815536877,"score_spread":0.2253123219510059,"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."}}