{"id":"W2079653584","doi":"10.1016/j.buildenv.2015.03.010","title":"Impact of residential building regulations on reducing indoor exposures to outdoor PM 2.5 in Toronto","year":2015,"lang":"en","type":"article","venue":"Building and Environment","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Retrofitting; Valuation (finance); Capital cost; Building code; Environmental science; Environmental health; Business; Engineering; Civil engineering; Finance; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007945445,0.0001586431,0.0002185225,0.00005637671,0.00009964303,0.0000215918,0.0001276891,0.0000790296,0.0003024882],"category_scores_gemma":[0.0001220656,0.0001445018,0.00004795729,0.00008549171,0.00007978833,0.0002128211,0.0001797436,0.0001012241,0.00003362929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001497101,"about_ca_system_score_gemma":0.00002313482,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02104724,"about_ca_topic_score_gemma":0.0004439216,"domain_scores_codex":[0.9984352,0.00009955141,0.0003707945,0.0003505621,0.0003781702,0.0003657369],"domain_scores_gemma":[0.9991596,0.00006230901,0.0001063632,0.0002722257,0.000002326882,0.0003971468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0009179818,0.0006725765,0.3983941,0.00005844845,0.00004475091,0.00001509851,0.01557555,0.4457924,0.05070946,0.0007713796,0.01358602,0.07346214],"study_design_scores_gemma":[0.0006195086,0.0007429487,0.9934759,0.000105543,0.000009205939,0.000004139788,0.0003695542,0.0008769524,0.001778011,0.0004631835,0.001352096,0.0002030169],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996949,0.0001181709,0.0007100785,0.0009518864,0.00006731594,0.0002633727,0.000006016613,0.00001539883,0.0009187723],"genre_scores_gemma":[0.9903696,0.00004673169,0.00914926,0.0002162732,0.00006310652,0.00001613728,0.000001608859,0.00001497215,0.0001223343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5950817,"threshold_uncertainty_score":0.9854717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04657660856643974,"score_gpt":0.3449313632109244,"score_spread":0.2983547546444847,"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."}}