{"id":"W4247919137","doi":"10.31124/advance.13517291.v1","title":"Constructing Gender-responsive COVID-19 SME Recovery Measures","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Entrepreneurship Studies and Influences","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Entrepreneurship; Coronavirus disease 2019 (COVID-19); Embodied cognition; Pandemic; Feminism; Gender equality; Political science; Women entrepreneurs; 2019-20 coronavirus outbreak; Public relations; Sociology; Economic growth; Business; Economics; Gender studies; Computer science; Medicine; Law","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":[0.01654131,0.0003713155,0.0003259441,0.002422401,0.003133017,0.004908658,0.001715555,0.001433407,0.004304621],"category_scores_gemma":[0.02794485,0.0002757375,0.0003828656,0.001801445,0.005552394,0.004770425,0.006400476,0.002105424,0.0004241129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007875335,"about_ca_system_score_gemma":0.01201485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002533229,"about_ca_topic_score_gemma":0.006048622,"domain_scores_codex":[0.9884227,0.006160195,0.0006117084,0.0007172172,0.002553998,0.001534328],"domain_scores_gemma":[0.9878896,0.005185521,0.002108478,0.001900816,0.002165561,0.0007500211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009151617,0.0002537071,0.009270336,0.000397575,0.00002902657,0.0003382757,0.0192148,0.004633817,0.002147875,0.8279603,0.006280982,0.1293819],"study_design_scores_gemma":[0.00008901375,0.0008465088,0.05253796,0.001747039,0.00009949102,0.0002589225,0.1252775,0.01304741,0.01779095,0.4070399,0.3810919,0.0001733718],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4464897,0.001152588,0.1027264,0.0262873,0.0004424954,0.002260997,0.0004566415,0.0004044196,0.4197793],"genre_scores_gemma":[0.965921,0.0002545799,0.02504387,0.0007626132,0.00002794237,0.0005110727,0.0001107477,0.00003706659,0.007331008],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01654131,"threshold_uncertainty_score":0.08747989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08565698469526181,"score_gpt":0.2878288944385226,"score_spread":0.2021719097432608,"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."}}