{"id":"W1966411352","doi":"10.1111/ina.12088","title":"Particle characterization in retail environments: concentrations, sources, and removal mechanisms","year":2013,"lang":"en","type":"article","venue":"Indoor Air","topic":"Infection Control and Ventilation","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Texas at Austin; Pennsylvania State University; Texas Commission on Environmental Quality","keywords":"Environmental science; Ventilation (architecture); Particle (ecology); Particle size; Air filtration; Filtration (mathematics); Indoor air; Environmental engineering; Mass concentration (chemistry); Particle number; Indoor air quality; Ultrafine particle; Environmental chemistry; Chemistry; Materials science; Meteorology; Statistics; Ecology; Geography; Mathematics; Physics; Nanotechnology","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":[0.0005664228,0.0003888691,0.0003700991,0.0005805389,0.0005252543,0.001176047,0.000647696,0.000765141,0.001612513],"category_scores_gemma":[0.0006816062,0.0002098343,0.0002646566,0.0007366742,0.0005055013,0.0005801746,0.0004528426,0.0002860757,0.0004983541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004632909,"about_ca_system_score_gemma":0.0002708146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00354959,"about_ca_topic_score_gemma":0.003516521,"domain_scores_codex":[0.9995044,0.00005080102,0.00004583157,0.0001952027,0.0001386232,0.0000651296],"domain_scores_gemma":[0.9993426,0.0001530284,0.0002695202,0.00004191727,0.0001656934,0.00002725534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009297744,0.0003803241,0.5412128,0.001486983,0.000146255,0.0004865067,0.001081742,0.001616341,0.380567,0.0002597058,0.0009392085,0.07089344],"study_design_scores_gemma":[0.00001634195,0.0007846495,0.842196,0.0001223302,0.0001280793,0.001422177,0.001341348,0.003143554,0.1465723,0.0002683634,0.003973088,0.00003163679],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902519,0.003083795,0.004607435,0.00007054578,0.0000168893,0.00005858772,0.0005113056,0.00006063364,0.001338898],"genre_scores_gemma":[0.99447,0.000839222,0.003524276,0.00004813218,0.000017802,0.0000294431,0.0004862993,0.00001646689,0.0005684902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00354959,"threshold_uncertainty_score":0.007057846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009557974379326005,"score_gpt":0.212448722990085,"score_spread":0.202890748610759,"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."}}