{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008626723,0.0003367701,0.0002732133,0.0003516504,0.0009052886,0.003032351,0.0004666967,0.001538548,0.02526202],"category_scores_gemma":[0.004408137,0.0001130195,0.0002953257,0.0004625787,0.00101903,0.001741276,0.0009354358,0.002175262,0.0008225791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001246976,"about_ca_system_score_gemma":0.001046721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009229532,"about_ca_topic_score_gemma":0.02486418,"domain_scores_codex":[0.999818,0.00005070533,0.000007314736,0.00003537906,0.00004892895,0.00003971516],"domain_scores_gemma":[0.9977177,0.001351733,0.0002857998,0.00004386984,0.0002255229,0.0003754022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007078491,0.002818524,0.2842908,0.001315033,0.0002470692,0.001167693,0.01189119,0.008426801,0.003721776,0.04221431,0.07262646,0.5705725],"study_design_scores_gemma":[0.0001019681,0.0008707988,0.5116991,0.002540949,0.0004199969,0.001332959,0.06582764,0.006228552,0.00586385,0.2327816,0.1721341,0.0001985572],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.71141,0.03129767,0.003013118,0.1244733,0.001648167,0.00004343382,0.0005086589,0.0000639698,0.1275417],"genre_scores_gemma":[0.9380528,0.02665759,0.00054184,0.003275017,0.001295147,0.00002243043,0.0001849434,0.00002077111,0.02994957],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02526202,"threshold_uncertainty_score":0.08450991,"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."}}