{"id":"W4205273121","doi":"10.1007/s10453-021-09732-5","title":"Microbial composition of bioaerosols in indoor wastewater treatment plants","year":2022,"lang":"en","type":"article","venue":"Aerobiologia","topic":"Indoor Air Quality and Microbial Exposure","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut de recherche Robert-Sauvé en santé et en sécurité du travail; Université Laval; Institut universitaire de cardiologie et de pneumologie de Québec","funders":"Institut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail","keywords":"Indoor bioaerosol; Bioaerosol; Sewage treatment; Wastewater; Environmental science; Sewage; Amplicon sequencing; Contamination; Actinobacteria; Microorganism; Biology; Waste management; Ecology; Environmental engineering; Bacteria; 16S ribosomal RNA; Chemistry; Aerosol","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002073143,0.0001139447,0.00018259,0.00003223323,0.0001108596,0.000005122147,0.0001785595,0.00005717895,0.001930606],"category_scores_gemma":[0.000002468611,0.00009646139,0.00005784281,0.0001180316,0.0001289986,0.00005036104,0.0002127643,0.0001080204,0.0001249594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002884808,"about_ca_system_score_gemma":0.00001028886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001022791,"about_ca_topic_score_gemma":0.0002121991,"domain_scores_codex":[0.9990167,0.0001986047,0.0002564022,0.0002291842,0.00006870674,0.0002304145],"domain_scores_gemma":[0.9997016,0.00002856551,0.00008699106,0.0001573472,0.000001878767,0.00002363803],"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":[0.0001468193,0.0002977076,0.02329804,0.000002460226,0.000008294524,0.000009791351,0.0008262419,0.0007668828,0.9729449,0.00003128891,0.001137296,0.0005303413],"study_design_scores_gemma":[0.002219877,0.001354337,0.02228758,0.0000136482,0.000009825902,0.00006740367,0.000489452,0.00002315598,0.9628512,0.0000784301,0.01029352,0.0003115394],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985621,0.00001341891,0.000003444622,0.0001656929,0.0001606619,0.0002731258,0.0001787346,0.0000172721,0.0006255317],"genre_scores_gemma":[0.9990837,0.000005491876,0.0002150765,0.000216565,0.000009412383,0.0000317148,0.0001903081,0.000006297056,0.0002414085],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0100936,"threshold_uncertainty_score":0.9989818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01501857192597383,"score_gpt":0.2243717991337683,"score_spread":0.2093532272077945,"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."}}