{"id":"W2616964574","doi":"10.1016/j.scitotenv.2017.05.076","title":"Bioaerosol sampling and detection methods based on molecular approaches: No pain no gain","year":2017,"lang":"en","type":"review","venue":"The Science of The Total Environment","topic":"Indoor Air Quality and Microbial Exposure","field":"Environmental Science","cited_by":74,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Institut universitaire de cardiologie et de pneumologie de Québec","funders":"","keywords":"Indoor bioaerosol; Bioaerosol; Standardization; Biochemical engineering; Sampling (signal processing); Environmental science; Computational biology; Computer science; Biology; Ecology; Chemistry; Engineering","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":[0.001618177,0.001426282,0.002291085,0.002163694,0.0002252754,0.001457817,0.00146212,0.001688584,0.002340212],"category_scores_gemma":[0.001345697,0.0004599215,0.0009266037,0.001734031,0.00113298,0.002337732,0.001037881,0.002181965,0.001655537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006722423,"about_ca_system_score_gemma":0.001350323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008554938,"about_ca_topic_score_gemma":0.00166821,"domain_scores_codex":[0.9992256,0.0001004522,0.0000705707,0.0001615672,0.0003871359,0.00005476411],"domain_scores_gemma":[0.9993075,0.0003330596,0.00009946276,0.00004115469,0.0001898248,0.00002898017],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001370462,0.000104955,0.0003994554,0.02074185,0.0001709832,0.0001642529,0.00005534484,0.0003209065,0.01272711,0.008187484,0.01109177,0.9458989],"study_design_scores_gemma":[0.00002753092,0.000258066,0.001811738,0.004016636,0.0003474239,0.001651299,0.0001393676,0.0003753737,0.01685531,0.0061852,0.9682546,0.00007753965],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003221674,0.9964307,0.001304673,0.0003905531,0.0004078506,0.000009407936,0.00003217515,0.00001136688,0.001091086],"genre_scores_gemma":[0.003544369,0.9922405,0.001737756,0.0004278402,0.0003582136,0.0000164652,0.00005989099,0.000006620896,0.00160831],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002340212,"threshold_uncertainty_score":0.008557856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08807835086570144,"score_gpt":0.3202381576984245,"score_spread":0.2321598068327231,"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."}}