{"id":"W3039898849","doi":"10.1016/j.scs.2020.102371","title":"The contribution of dry indoor built environment on the spread of Coronavirus: Data from various Indian states","year":2020,"lang":"en","type":"article","venue":"Sustainable Cities and Society","topic":"Infection Control and Ventilation","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Department of Science and Technology, Republic of the Philippines; Ministry of Education, India; Department of Science and Technology, Ministry of Science and Technology, India","keywords":"Metropolitan area; Environmental science; Coronavirus; Coronavirus disease 2019 (COVID-19); Transmission (telecommunications); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Population; Indoor air quality; Environmental engineering; Meteorology; Geography; Environmental health; Computer science; Telecommunications","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":[0.0004152285,0.0002302842,0.0001867261,0.001331744,0.000795998,0.0009626853,0.0004691299,0.0002391299,0.001177322],"category_scores_gemma":[0.0009862328,0.0001811301,0.0005832643,0.003047409,0.0005945641,0.0002842872,0.0007869409,0.0005457696,0.000132673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005240348,"about_ca_system_score_gemma":0.0008465125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0849084,"about_ca_topic_score_gemma":0.1307459,"domain_scores_codex":[0.999658,0.00009827133,0.00004036953,0.00004432639,0.00006007206,0.00009890286],"domain_scores_gemma":[0.998853,0.0002246287,0.0003509901,0.0001186583,0.0002547456,0.0001980554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008272408,0.00003661995,0.9934098,0.00003839279,0.00006745962,0.00007208465,0.001726109,0.00007959678,0.0002987171,0.00007816614,0.000140333,0.003969898],"study_design_scores_gemma":[8.363711e-7,0.00004259867,0.9956339,0.000008754565,0.00004997502,0.00007388866,0.003659272,0.00004791923,0.00008202014,0.0000203715,0.0003754826,0.000004887737],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967582,0.000229401,0.00009839913,0.00006121861,0.000006112821,0.0000105889,0.0009657773,0.000004150873,0.001866181],"genre_scores_gemma":[0.9990473,0.0002714899,0.00005674031,0.00002648242,0.000005206671,0.000007113141,0.0004011932,0.000002050496,0.0001822805],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0849084,"threshold_uncertainty_score":0.1688284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02141887039697826,"score_gpt":0.2562823895937906,"score_spread":0.2348635191968124,"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."}}