{"id":"W4410298533","doi":"10.3390/atmos16050574","title":"Indoor Air Quality Assessment Through IoT Sensor Technology: A Montreal–Qatar Case Study","year":2025,"lang":"en","type":"article","venue":"Atmosphere","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick; Concordia University","funders":"Qatar University; Concordia University","keywords":"Air quality index; Environmental science; Internet of Things; Remote sensing; Indoor air quality; Meteorology; Quality (philosophy); Computer science; Geography; Environmental engineering; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009311155,0.0005713298,0.0002391071,0.0008012491,0.001680327,0.001244438,0.0009073858,0.00106471,0.002621257],"category_scores_gemma":[0.001105018,0.00014664,0.0003398426,0.001583467,0.0007032526,0.0005203732,0.000748617,0.0004435608,0.000347078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00695178,"about_ca_system_score_gemma":0.003228202,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5355688,"about_ca_topic_score_gemma":0.6078991,"domain_scores_codex":[0.9992037,0.0002404866,0.00003435044,0.0001116605,0.0002457816,0.0001640904],"domain_scores_gemma":[0.9994166,0.0001527411,0.00005627629,0.00004615372,0.0002427189,0.00008559621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001062086,0.002766975,0.4224767,0.0009793612,0.000318166,0.06748611,0.00978185,0.1208114,0.03652475,0.02629054,0.03721898,0.274283],"study_design_scores_gemma":[0.0003586294,0.002701991,0.5514718,0.0004198223,0.0003744504,0.01026066,0.03054258,0.241431,0.0239611,0.004159239,0.1339361,0.0003825848],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9372863,0.001002097,0.01497637,0.002651916,0.00006570393,0.0007930802,0.001793379,0.0003117427,0.04111948],"genre_scores_gemma":[0.9839683,0.0003428319,0.008042905,0.0002067372,0.00001891593,0.00008152606,0.0003578801,0.00001989636,0.006961102],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4644312,"threshold_uncertainty_score":0.9343326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03046822967173378,"score_gpt":0.3381918743945173,"score_spread":0.3077236447227835,"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."}}