{"id":"W4402877670","doi":"10.1080/10807039.2024.2407137","title":"Combining biomonitoring data in children and biokinetic modeling to guide decision-making for health risk management – a case study on lead emitted by a smelter in Rouyn-Noranda, Canada","year":2024,"lang":"en","type":"article","venue":"Human and Ecological Risk Assessment An International Journal","topic":"Heavy Metal Exposure and Toxicity","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Institut National de Santé Publique du Québec","funders":"","keywords":"Biomonitoring; Environmental health; Lead smelting; Environmental science; Environmental planning; Smelting; Environmental chemistry; Medicine; Chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001090553,0.000930028,0.0005540607,0.0004451951,0.001458821,0.001544978,0.001302605,0.001287605,0.001878719],"category_scores_gemma":[0.001443361,0.0004181227,0.0009420539,0.0008791274,0.0008774871,0.0004597389,0.0006974812,0.0009266545,0.0001729186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01489202,"about_ca_system_score_gemma":0.0181066,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9367505,"about_ca_topic_score_gemma":0.9451093,"domain_scores_codex":[0.9993788,0.0001860084,0.00002328286,0.00009955973,0.0001585495,0.0001537497],"domain_scores_gemma":[0.9992448,0.0003801423,0.00004530917,0.00003462184,0.0002227286,0.00007245662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002319091,0.0002396134,0.06613617,0.0001241446,0.0001172867,0.001095073,0.0005513997,0.9078218,0.002544242,0.002280521,0.001224244,0.01763352],"study_design_scores_gemma":[0.0001234136,0.0004318045,0.03915655,0.00007424086,0.0001434425,0.0002099582,0.00349258,0.9366176,0.006308017,0.001676625,0.01163958,0.0001262972],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9741483,0.0002900068,0.01249779,0.0007850694,0.00001941508,0.0002528889,0.001317943,0.0001457905,0.01054291],"genre_scores_gemma":[0.9761949,0.0003131572,0.0180912,0.00008388337,0.000005078043,0.00006795998,0.0005944028,0.00003689202,0.004612436],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06324953,"threshold_uncertainty_score":0.127244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03606740870040599,"score_gpt":0.4068463537979657,"score_spread":0.3707789450975598,"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."}}