{"id":"W3125787765","doi":"","title":"TECHNOLOGY ADOPTION: A SOLUTION FOR SMES TO OVERCOME PROBLEMS DURING COVID- 19","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; Salary; Revenue; Coronavirus disease 2019 (COVID-19); Cash flow; Small and medium-sized enterprises; Cash; China; Supply chain; Commerce; Marketing; Finance; Economics; Market economy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003798452,0.0005518402,0.0003352271,0.001040049,0.004206812,0.00721229,0.001458552,0.005197387,0.01398663],"category_scores_gemma":[0.01232619,0.000236145,0.0006522745,0.001249493,0.001597538,0.008107523,0.008287972,0.004643124,0.00356967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001863771,"about_ca_system_score_gemma":0.00906757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003028805,"about_ca_topic_score_gemma":0.003997283,"domain_scores_codex":[0.9964535,0.001176534,0.0001731369,0.0002687941,0.0006996227,0.0012283],"domain_scores_gemma":[0.989546,0.001535645,0.001482896,0.0006284614,0.002296424,0.00451064],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000183275,0.001549165,0.0542196,0.001011046,0.00008968053,0.00604091,0.06215198,0.001094276,0.008330428,0.1271006,0.1915984,0.5466306],"study_design_scores_gemma":[0.0001042469,0.0009496416,0.04501585,0.001483939,0.00006865241,0.002135636,0.1328329,0.003331653,0.001991151,0.04408728,0.7678777,0.000121265],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3286049,0.003771543,0.02167812,0.4575064,0.001940858,0.0004620508,0.0001573166,0.0007192119,0.1851597],"genre_scores_gemma":[0.9154833,0.002860806,0.01110492,0.02123572,0.0006799612,0.0002677786,0.0002022298,0.00009764822,0.04806755],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01398663,"threshold_uncertainty_score":0.04678988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04011913146014008,"score_gpt":0.2622124179026059,"score_spread":0.2220932864424658,"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."}}