{"id":"W4411801183","doi":"10.1007/s10653-025-02604-8","title":"Mobilization of mercury, thallium and arsenic in soil hydrological processes in karst catchment, southwest China","year":2025,"lang":"en","type":"article","venue":"Environmental Geochemistry and Health","topic":"Thallium and Germanium Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"State Key Laboratory of Environmental Geochemistry; National Natural Science Foundation of China","keywords":"Karst; Mercury (programming language); Thallium; Drainage basin; Arsenic; China; Environmental science; Hydrology (agriculture); Mobilization; Geology; Geography; Chemistry; Archaeology; Geotechnical engineering","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":[0.0002259271,0.0002366738,0.0002895026,0.001040383,0.0008163701,0.0005669611,0.0004419089,0.0003260193,0.0003826458],"category_scores_gemma":[0.0002426579,0.0002601371,0.0002882468,0.001145282,0.0004439728,0.0004472125,0.0005022106,0.0001610773,0.00005071281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001573476,"about_ca_system_score_gemma":0.001726496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1810696,"about_ca_topic_score_gemma":0.193138,"domain_scores_codex":[0.9998825,0.00001342484,0.00001126825,0.0000394116,0.00001973361,0.0000335469],"domain_scores_gemma":[0.9998546,0.00001854501,0.00003815298,0.000007492009,0.00003648173,0.00004476481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002111127,0.00008317597,0.9707366,0.00004822467,0.00008630113,0.0003479437,0.00214321,0.001125155,0.01958237,0.0001726814,0.00009812392,0.005364964],"study_design_scores_gemma":[0.000005450665,0.00002017818,0.9979526,0.000001858773,0.00001643309,0.0000310679,0.0006279028,0.0008843919,0.000330504,0.000034664,0.00009040476,0.0000045443],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998575,0.00001710646,0.00001929908,0.00000809359,3.769366e-7,0.000001215491,0.00002686423,0.000001428208,0.00006810415],"genre_scores_gemma":[0.9997405,0.00002157814,0.00002630387,0.000004435688,0.000001206234,0.00000218217,0.00004974607,5.082595e-7,0.0001534901],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1810696,"threshold_uncertainty_score":0.3600314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008567275013007872,"score_gpt":0.2454645659735851,"score_spread":0.2368972909605772,"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."}}