{"id":"W2508414066","doi":"10.1016/j.envres.2016.07.040","title":"Mercury concentrations in urine of amerindian populations near oil fields in the peruvian and ecuadorian amazon","year":2016,"lang":"en","type":"article","venue":"Environmental Research","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal; McGill University","funders":"","keywords":"Mercury (programming language); Urine; Creatinine; Amazon rainforest; Environmental chemistry; Animal science; Environmental science; Chemistry; Geography; Biology; Ecology; Biochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005571001,0.00007823464,0.00009864736,0.000059157,0.0001593776,0.0000174235,0.0001541929,0.00004275296,0.001590352],"category_scores_gemma":[0.00008135525,0.00005004263,0.00002099396,0.0002126339,0.000814562,0.0001744302,0.0001381813,0.0001624223,0.0001543662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001315213,"about_ca_system_score_gemma":0.000008968887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001236753,"about_ca_topic_score_gemma":0.003433614,"domain_scores_codex":[0.9986866,0.0002124385,0.000200157,0.0001856303,0.0004267676,0.0002883824],"domain_scores_gemma":[0.9995231,0.0001847635,0.00002991888,0.0001920377,0.000001528811,0.00006863662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001169203,0.000121518,0.9416309,0.000003609215,0.000002598089,0.00000665428,0.004205888,0.00001958022,0.01220029,0.0001315234,0.0001148139,0.04155092],"study_design_scores_gemma":[0.0003809922,0.0001055144,0.9914982,0.00002146176,0.000002004172,0.000003230527,0.003073861,0.0000361622,0.001006668,0.0005945794,0.003204774,0.00007252657],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925297,0.0001074539,0.000007302267,0.002463987,0.00002200506,0.0001534073,0.00001953449,0.000002459606,0.004694143],"genre_scores_gemma":[0.9984955,0.000704043,0.00008232737,0.00005587634,0.0000148558,0.00003894889,0.000004667199,0.000005725439,0.0005980631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04986731,"threshold_uncertainty_score":0.9993224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05257389959472109,"score_gpt":0.338746771669978,"score_spread":0.2861728720752569,"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."}}