{"id":"W4377229893","doi":"10.3386/w31255","title":"Stress Relief?: Funding Structures and Resilience to the Covid Shock","year":2023,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Resilience (materials science); Shock (circulatory); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Stress (linguistics); Medicine; Virology; Materials science; Internal medicine; Outbreak; Philosophy; Composite material; Linguistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009173188,0.0001500657,0.0002635879,0.0006881274,0.0009099937,0.0003262431,0.001258634,0.0002043423,0.0002772501],"category_scores_gemma":[0.00439888,0.0001182111,0.00007497639,0.0005083088,0.0009329465,0.0001827304,0.0006119567,0.0004607832,0.0001471831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009615686,"about_ca_system_score_gemma":0.003036536,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01012645,"about_ca_topic_score_gemma":0.01778958,"domain_scores_codex":[0.995371,0.0003489672,0.0004237808,0.000571338,0.002741407,0.000543463],"domain_scores_gemma":[0.996851,0.00170899,0.0001831361,0.0002976934,0.0007551223,0.0002040783],"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":[0.00002796069,0.00001592123,0.002755471,0.0001499446,0.00006776059,0.000004770635,0.002564151,0.001674141,0.000008425448,0.5114839,0.4771855,0.004062044],"study_design_scores_gemma":[0.0001679266,0.00008656768,0.008179191,0.0001923846,0.00001726997,0.000002516747,0.008210032,0.0001017508,0.0000157251,0.2361531,0.7465553,0.0003182552],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.006901855,0.0005528264,0.000006955177,0.01112374,0.00125834,0.001068138,0.0001176225,0.00004028994,0.9789302],"genre_scores_gemma":[0.809394,0.005232569,0.00007611639,0.0001233792,0.002280904,0.0001326002,0.00008540979,0.00004169034,0.1826333],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8024921,"threshold_uncertainty_score":0.9964652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4026264025187333,"score_gpt":0.551143425327388,"score_spread":0.1485170228086548,"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."}}