{"id":"W2980608261","doi":"10.1080/02786826.2019.1682509","title":"Natural sources and experimental generation of bioaerosols: Challenges and perspectives","year":2019,"lang":"en","type":"article","venue":"Aerosol Science and Technology","topic":"Indoor Air Quality and Microbial Exposure","field":"Environmental Science","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Vetenskapsrådet; Ministry of Defense; AFA Försäkring; Svenska Forskningsrådet Formas; Richard and Susan Smith Family Foundation","keywords":"Aerosol; Bioaerosol; Indoor bioaerosol; Environmental science; Biochemical engineering; Characterization (materials science); Natural (archaeology); Process engineering; Computer science; Meteorology; Nanotechnology; Engineering; Geography; Materials 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002345818,0.00007963144,0.0001111617,0.00005834311,0.0001531577,0.00002066415,0.0001212288,0.0000753645,0.00003024953],"category_scores_gemma":[0.00003037242,0.00006633498,0.00000733,0.0001910957,0.002542459,0.0002864132,0.000265943,0.00007815394,0.000007381705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002425536,"about_ca_system_score_gemma":0.00001027072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005157878,"about_ca_topic_score_gemma":0.00005695807,"domain_scores_codex":[0.9992478,0.00001248154,0.00009143494,0.0003458536,0.0001336513,0.0001687873],"domain_scores_gemma":[0.9997736,0.00001145756,0.00004635302,0.0001196984,0.00001719413,0.00003168583],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000003663058,0.00002118703,0.002122192,0.000004504551,0.000001813404,3.174494e-7,0.00341359,4.676969e-7,0.9816192,0.005178916,0.000009443006,0.00762466],"study_design_scores_gemma":[0.0003292001,0.0003419013,0.002962445,0.00001009481,0.000003418159,0.0000437763,0.01436666,0.0002000301,0.9811912,0.0002348324,0.0001756657,0.0001407639],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918811,0.005939293,0.000001795466,0.001343399,0.00005129044,0.0001305426,0.000001007358,0.00002347605,0.0006280894],"genre_scores_gemma":[0.9990503,0.0005226259,0.0003036374,0.0000448631,0.000008377596,0.000003811434,2.789842e-7,0.000002874084,0.000063262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01095307,"threshold_uncertainty_score":0.9367797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0189026769081328,"score_gpt":0.2363229663686032,"score_spread":0.2174202894604704,"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."}}