{"id":"W4415718888","doi":"10.1007/s11356-025-37030-x","title":"Heavy metal contamination in urban agriculture: evidence from Nairobi","year":2025,"lang":"en","type":"article","venue":"Environmental Science and Pollution Research","topic":"Heavy metals in environment","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"International Fine Particle Research Institute; Consortium of International Agricultural Research Centers; National Commission for Science, Technology and Innovation; U.S. Department of Health and Human Services","keywords":"Leafy vegetables; Contamination; Cadmium; Mercury (programming language); Agriculture; Population; Heavy metals; Ecotoxicology","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":[0.001036923,0.0003711227,0.0003741475,0.001769886,0.00148336,0.001063412,0.0007833481,0.0005053819,0.001682698],"category_scores_gemma":[0.002733934,0.000546397,0.000352629,0.004259737,0.00149733,0.0003872324,0.001646382,0.0003355814,0.0002670723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001782797,"about_ca_system_score_gemma":0.002482234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3512444,"about_ca_topic_score_gemma":0.5612674,"domain_scores_codex":[0.9991065,0.0002598897,0.0000907996,0.0001379256,0.0002038313,0.0002010942],"domain_scores_gemma":[0.9982033,0.0002536198,0.0009402149,0.0001639444,0.0002910698,0.0001478807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008882417,0.000064323,0.9887673,0.0002026297,0.00009525717,0.0002962681,0.003058029,0.00004133403,0.0009711785,0.0001260526,0.000285679,0.006003027],"study_design_scores_gemma":[0.000007486414,0.00002292053,0.9975017,0.00005905392,0.00003785973,0.0001071483,0.001481547,0.00003999212,0.00007449369,0.00001926492,0.0006446213,0.000003994856],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945985,0.00109379,0.0001321371,0.0003109699,0.000004441682,0.0000404342,0.0006221076,0.000003601573,0.003194146],"genre_scores_gemma":[0.9975116,0.001388513,0.0001845014,0.0001633836,0.000005469282,0.0000302417,0.0003533436,0.000003637093,0.0003592257],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3512444,"threshold_uncertainty_score":0.6983998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03025054656318085,"score_gpt":0.3214723024838296,"score_spread":0.2912217559206488,"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."}}