{"id":"W2963258879","doi":"10.1021/acs.est.9b03869","title":"Learning from the Past: Fires, Architecture, and Environmental Lead Emissions","year":2019,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Heavy metals in environment","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Architecture; Humanities; Archaeology; Library science; Geography; Art; Computer science","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":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006554889,0.00042123,0.0003064096,0.000149038,0.001001002,0.00006784133,0.001446815,0.0002350348,0.006688218],"category_scores_gemma":[0.00006885413,0.0003148385,0.00008100775,0.0005787253,0.006761265,0.0003745131,0.00281889,0.0009238609,0.003801591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007017699,"about_ca_system_score_gemma":0.00001324796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001071763,"about_ca_topic_score_gemma":0.00001244549,"domain_scores_codex":[0.9960691,0.0001223582,0.0003880999,0.001359813,0.001076668,0.0009839963],"domain_scores_gemma":[0.9983085,0.0001825806,0.0001757924,0.001072139,5.471544e-7,0.0002603899],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000008974443,0.0000981376,0.5474189,9.129454e-7,0.000008690242,0.000008282344,0.0004032317,0.001471754,0.4063633,0.00002567327,0.0001297472,0.04406238],"study_design_scores_gemma":[0.0008186193,0.0004882388,0.760635,0.00002633961,0.0000458353,0.0001315582,0.003714085,0.002181985,0.04086571,0.002041365,0.1881555,0.0008957141],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936488,0.0004144429,0.0002154871,0.002045901,0.0001979999,0.0006122978,0.0000261313,0.000134848,0.002704107],"genre_scores_gemma":[0.9957935,0.0003032904,0.001496654,0.0004879391,0.00005315263,0.00005525435,0.0000231019,0.00004216926,0.001744954],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3654976,"threshold_uncertainty_score":0.9999304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005193892608687228,"score_gpt":0.1988876163062996,"score_spread":0.1936937236976124,"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."}}