{"id":"W4328095041","doi":"10.54691/bcpbm.v38i.3738","title":"The Effect of COVID-19 Pandemic on Different Industries","year":2023,"lang":"en","type":"article","venue":"BCP Business & Management","topic":"COVID-19 and Mental Health","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Government (linguistics); Pandemic; Order (exchange); Business; Work (physics); Point (geometry); 2019-20 coronavirus outbreak; The Internet; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Shut down; Contagious disease; Economic growth; Economics; Disease; Engineering; Infectious disease (medical specialty); Virology; Finance; Medicine; Computer 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004259583,0.0002000684,0.0001443388,0.001292298,0.001201689,0.001660794,0.0003040716,0.0009433213,0.00875318],"category_scores_gemma":[0.001377831,0.00008500803,0.0003941596,0.001062015,0.0006907063,0.001028156,0.001443882,0.001275303,0.0007243137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001455585,"about_ca_system_score_gemma":0.001178123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01412084,"about_ca_topic_score_gemma":0.02632193,"domain_scores_codex":[0.999451,0.0001398234,0.00001910915,0.00004322662,0.0001231992,0.000223668],"domain_scores_gemma":[0.9990082,0.0001210223,0.0002464097,0.00002629475,0.000199664,0.0003984177],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005615339,0.0005734879,0.5659266,0.0009299222,0.000175967,0.004166045,0.006836892,0.0006800074,0.002134213,0.02720988,0.1061841,0.2846214],"study_design_scores_gemma":[0.00001679829,0.0004222154,0.8532229,0.001185964,0.0001117364,0.002124144,0.02785204,0.000719686,0.0008228142,0.007778238,0.1056682,0.00007530512],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7484106,0.04065965,0.000722966,0.07958743,0.002052832,0.0001066345,0.003396007,0.00009259499,0.1249713],"genre_scores_gemma":[0.9624447,0.02293828,0.0004358904,0.005482539,0.0007812044,0.00002902792,0.0005190455,0.00001369462,0.007355699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01412084,"threshold_uncertainty_score":0.02928233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09748538877463866,"score_gpt":0.4180509207159666,"score_spread":0.3205655319413279,"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."}}