{"id":"W2006196541","doi":"10.1177/1420326x11428164","title":"Risk-Based Prioritisation of Indoor Air Pollution Monitoring Using Computational Fluid Dynamics","year":2011,"lang":"en","type":"article","venue":"Indoor and Built Environment","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Environmental science; Indoor air quality; Pollutant; Computational fluid dynamics; Air pollution; Pollution; Environmental engineering; Air quality index; Contamination; Health risk; Airflow; Meteorology; Engineering; Environmental health","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":[],"consensus_categories":[],"category_scores_codex":[0.0001390758,0.000131646,0.0001370523,0.00003525565,0.0001790924,0.00000577304,0.00007591379,0.00005574273,0.000141947],"category_scores_gemma":[0.000008977501,0.0001253668,0.00004389118,0.0000601404,0.0002297238,0.0001251435,0.0001115147,0.00007914298,0.00001897105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002056505,"about_ca_system_score_gemma":0.000006644084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006647288,"about_ca_topic_score_gemma":0.00001479137,"domain_scores_codex":[0.999068,0.0000406651,0.0002236774,0.0002278379,0.0002705655,0.0001693084],"domain_scores_gemma":[0.9996734,0.00002254319,0.0001324449,0.0001113623,0.000003058988,0.00005714654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002807028,0.000144206,0.9512266,0.00001030648,0.0000184013,0.000002506918,0.0004838491,0.0300915,0.003688545,0.00002827047,0.000009937353,0.01426783],"study_design_scores_gemma":[0.0004910629,0.0000916586,0.9694809,0.00002145235,0.00003201919,0.000002741565,0.000161375,0.02165408,0.007371819,0.0004585266,0.00008879432,0.0001456274],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889241,0.00007888536,0.0103851,0.00005514496,0.00008901251,0.000152792,0.00003161231,0.00001496724,0.000268325],"genre_scores_gemma":[0.9865931,0.00004658878,0.01324795,0.00003044051,0.00004019932,0.000007265822,0.0000070069,0.00001024878,0.00001721679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01825427,"threshold_uncertainty_score":0.5112308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02040476422700156,"score_gpt":0.2218505721923399,"score_spread":0.2014458079653383,"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."}}