{"id":"W4283206104","doi":"10.1215/00703370-10047481","title":"Toxic Neighborhoods: The Effects of Concentrated Poverty and Environmental Lead Contamination on Early Childhood Development","year":2022,"lang":"en","type":"article","venue":"Demography","topic":"Heavy Metal Exposure and Toxicity","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Disadvantaged; Socioeconomic status; Poverty; Environmental health; Cognitive development; Psychology; Early childhood; Developmental psychology; Cognition; Geography; Gerontology; Population; Medicine; Economic growth; Economics","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":[0.0002171556,0.0001267477,0.0001303947,0.00003973302,0.0003075287,0.00001161231,0.0001564181,0.00003115553,0.0002422263],"category_scores_gemma":[0.00001546478,0.00009503242,0.00005927751,0.000248133,0.0001494051,0.00007836653,0.000139764,0.0001641151,0.00001572058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005914003,"about_ca_system_score_gemma":0.000007976268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003314525,"about_ca_topic_score_gemma":0.000006464529,"domain_scores_codex":[0.9988105,0.0001730337,0.0001858005,0.0002356392,0.000401632,0.0001933449],"domain_scores_gemma":[0.9995741,0.0001203839,0.00008900442,0.0001546106,0.000001265723,0.00006060403],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009255341,0.001248672,0.7671654,0.00002272566,0.0001633963,0.00001852659,0.006819075,0.00007440746,0.1065439,0.0004010939,0.000966761,0.1164835],"study_design_scores_gemma":[0.0005118202,0.0004456907,0.9568179,0.000005567493,0.00001635363,0.000003756677,0.0001864162,0.00004072819,0.03845,0.00007489522,0.003327436,0.0001194751],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979922,0.0001784709,0.00005278075,0.00007206298,0.0001043864,0.0003855901,0.00001291589,0.00001685161,0.001184724],"genre_scores_gemma":[0.9989936,0.00002384438,0.00004948308,0.0008047787,0.00000840089,0.00004476456,0.000016821,0.000009195892,0.00004914956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1896524,"threshold_uncertainty_score":0.387531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003307949027406029,"score_gpt":0.1716695848500429,"score_spread":0.1683616358226369,"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."}}