{"id":"W2018137071","doi":"10.1016/j.toxlet.2014.10.019","title":"Screening of population level biomonitoring data from the Canadian Health Measures Survey in a risk-based context","year":2014,"lang":"en","type":"article","venue":"Toxicology Letters","topic":"Effects and risks of endocrine disrupting chemicals","field":"Environmental Science","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada","funders":"","keywords":"Biomonitoring; Environmental health; Context (archaeology); Population; Risk assessment; Environmental science; Medicine; Geography; Environmental chemistry; Computer science; 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":[0.004623379,0.0005406721,0.0005033598,0.005116066,0.001290729,0.001200106,0.001504501,0.0003896039,0.001950098],"category_scores_gemma":[0.01465385,0.0001822706,0.0006347537,0.01230499,0.0004039547,0.0003217551,0.001142092,0.0005730961,0.0002303525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01132318,"about_ca_system_score_gemma":0.02510888,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9736562,"about_ca_topic_score_gemma":0.9835697,"domain_scores_codex":[0.9924666,0.001183896,0.0003566528,0.0004059426,0.005021409,0.0005654065],"domain_scores_gemma":[0.9935134,0.0007827464,0.0006641293,0.0003599148,0.004432364,0.0002475444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002111632,0.00008380751,0.919934,0.0006288322,0.0004724624,0.0003159058,0.00108437,0.00221831,0.00212716,0.002442604,0.01737597,0.05310538],"study_design_scores_gemma":[0.000008018174,0.0000373224,0.9833584,0.00004478154,0.00007620096,0.00005515177,0.0005520381,0.001083743,0.0006323233,0.0002430725,0.0138923,0.00001657592],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7498288,0.004631979,0.01603293,0.004150745,0.0001333619,0.001780928,0.1640675,0.000430348,0.05894336],"genre_scores_gemma":[0.9395493,0.001743748,0.01362326,0.000711947,0.00002586252,0.0003892914,0.04057991,0.00003330849,0.00334336],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02634382,"threshold_uncertainty_score":0.08215582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1067646865580172,"score_gpt":0.3688666690833446,"score_spread":0.2621019825253275,"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."}}