{"id":"W6950046050","doi":"10.5281/zenodo.5336250","title":"Study of the Negative & the Positive Impact of Coronavirus Pandemic on Different Types of Industry, Businesses & the Society","year":2021,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Diverse Scientific Research Studies","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pandemic; nobody; Population; Coronavirus disease 2019 (COVID-19); Public health; Coronavirus; Government (linguistics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001283093,0.0001313927,0.0002380451,0.00005440523,0.00303439,0.00006016057,0.001052278,0.00007808903,0.005234109],"category_scores_gemma":[0.003121009,0.00006287301,0.0001503206,0.001011591,0.0007344616,0.00007395379,0.002647534,0.0008557674,0.0003642572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001867256,"about_ca_system_score_gemma":0.00005452377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000364601,"about_ca_topic_score_gemma":0.00005003079,"domain_scores_codex":[0.9959305,0.00232874,0.0003697545,0.00026719,0.0007933418,0.0003104947],"domain_scores_gemma":[0.9959983,0.0006557132,0.0003606199,0.0007689872,0.002157949,0.0000584267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001038727,0.004203447,0.03090005,0.0005191314,0.003210423,0.000005683575,0.3223743,0.001278702,0.02977716,0.002693395,0.5829212,0.02107782],"study_design_scores_gemma":[0.001627085,0.0005591685,0.8259147,0.0003508397,0.0001264835,0.00000666175,0.07820716,0.00002988211,0.0008746065,0.0002683214,0.09186681,0.0001682748],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9826192,0.00006011419,0.00002316822,0.0008640012,0.0001475378,0.001127274,0.0005488521,0.00004226973,0.01456759],"genre_scores_gemma":[0.9958261,0.0001150836,0.000006294329,0.0000575885,0.00004624417,2.916243e-7,0.00007550382,0.000159693,0.003713256],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7950147,"threshold_uncertainty_score":0.9982635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2205421677757295,"score_gpt":0.4289434662827507,"score_spread":0.2084012985070212,"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."}}