{"id":"W2075152535","doi":"10.1016/j.envint.2014.10.007","title":"Environmental determinants of different blood lead levels in children: A quantile analysis from a nationwide survey","year":2014,"lang":"en","type":"article","venue":"Environment International","topic":"Heavy Metal Exposure and Toxicity","field":"Environmental Science","cited_by":57,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"Région Bretagne","keywords":"Quantile; Environmental health; Tap water; Confidence interval; Quantile regression; Lead exposure; Medicine; Environmental science; Toxicology; Environmental engineering; Statistics; Mathematics","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":[0.0004865547,0.0002172226,0.0003552041,0.0001453588,0.00004378749,0.00001772359,0.0004286802,0.00009045626,0.008033217],"category_scores_gemma":[0.00006702847,0.0002046561,0.000166776,0.0001425176,0.000164993,0.0001827542,0.0002699353,0.0001369542,0.0003315877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001306946,"about_ca_system_score_gemma":0.000003199999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001862481,"about_ca_topic_score_gemma":0.001335587,"domain_scores_codex":[0.997685,0.0002543518,0.0005713863,0.0005004517,0.000751336,0.000237523],"domain_scores_gemma":[0.9991748,0.0001805443,0.0002278519,0.0003294333,0.000001588321,0.00008579961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000175494,0.0006846365,0.9851909,5.977595e-7,0.0002073948,0.000001602361,0.00009134316,0.001045711,0.01017847,0.00001781841,0.000009493992,0.002554439],"study_design_scores_gemma":[0.0006624989,0.00006389368,0.9744303,0.000004980117,0.00009931686,0.000001540654,0.000006485723,0.005595522,0.01856835,0.0002609672,0.00010907,0.000197027],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967327,0.00001537319,0.001997932,0.0000254482,0.00008122435,0.000158958,0.0005189109,0.000009583178,0.0004598476],"genre_scores_gemma":[0.9987516,0.00003032097,0.0005521795,0.00007555311,0.00003822698,0.00001895759,0.0002973004,0.00001481541,0.0002210616],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01076059,"threshold_uncertainty_score":0.9928735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01498973667123318,"score_gpt":0.237214855714913,"score_spread":0.2222251190436798,"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."}}