{"id":"W2084846944","doi":"10.1371/journal.pone.0097805","title":"Determining Prenatal, Early Childhood and Cumulative Long-Term Lead Exposure Using Micro-Spatial Deciduous Dentine Levels","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Heavy Metal Exposure and Toxicity","field":"Environmental Science","cited_by":91,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Public Health Ontario","funders":"National Institute of Environmental Health Sciences; National Health and Medical Research Council; U.S. Public Health Service","keywords":"Medicine; Pregnancy; Physiology; Cord blood; Cohort; Deciduous teeth; Biomarker; Dentistry; Internal medicine; Chemistry; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.0002693064,0.0002214583,0.0003174065,0.00004302529,0.0002133895,0.00008036719,0.0001921421,0.0001116496,0.0002600717],"category_scores_gemma":[0.0001393758,0.0002124007,0.00005080609,0.000119211,0.0001715711,0.00038458,0.0002860501,0.0001954346,0.000140556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004984785,"about_ca_system_score_gemma":0.00001090167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002028262,"about_ca_topic_score_gemma":0.0001811575,"domain_scores_codex":[0.9983003,0.0001216125,0.0003070788,0.0004509526,0.0004324152,0.0003876503],"domain_scores_gemma":[0.9993219,0.00008790187,0.0001321608,0.0002773676,0.00001396637,0.0001667509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001283633,0.0004844676,0.7057549,0.00002665654,0.00006904353,0.00001463262,0.00109563,0.00002123601,0.2741304,0.000001477475,0.000001314893,0.0183874],"study_design_scores_gemma":[0.0005164812,0.0002216737,0.7760081,0.0001163096,0.00008041324,0.00001350538,0.000005944481,0.0008742708,0.2218955,0.00004414228,0.000002613302,0.000220985],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966461,0.00005868873,0.002520103,0.00002176495,0.00004017761,0.000278798,0.00001307625,0.00004974187,0.0003715386],"genre_scores_gemma":[0.9924948,0.000006476556,0.007052755,0.0001137351,0.0001403524,0.000007757057,0.000005264233,0.00003063401,0.0001482825],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07025322,"threshold_uncertainty_score":0.8661451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04718058032510758,"score_gpt":0.2458897441624145,"score_spread":0.1987091638373069,"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."}}