{"id":"W4321770418","doi":"10.18235/0004754","title":"The Causal Impact of Covid-19 Government-backed Loans on MSMEs Liquidity and Earnings","year":2023,"lang":"en","type":"report","venue":"","topic":"Business, Innovation, and Economy","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Loan; Market liquidity; Business; Government (linguistics); Earnings; Shock (circulatory); Coronavirus disease 2019 (COVID-19); Financial system; Finance; Medicine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002009989,0.0003247466,0.0007822296,0.0001827164,0.0002673926,0.0001192819,0.0002752046,0.0003201148,0.0008411082],"category_scores_gemma":[0.001434468,0.0002654746,0.0002391989,0.0003571869,0.0001946548,0.000151615,0.0001263864,0.0003186128,0.0002293153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001021081,"about_ca_system_score_gemma":0.0006411376,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01008949,"about_ca_topic_score_gemma":0.0006379721,"domain_scores_codex":[0.9978018,0.00001478204,0.001127899,0.0005576708,0.0001458886,0.0003519226],"domain_scores_gemma":[0.9973475,0.0003729243,0.001499471,0.000535754,0.0001263565,0.0001179387],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009029849,0.00008255491,0.7019715,0.0003976454,0.0006549134,0.000008976941,0.000242729,0.0002441545,0.000002745882,0.008660486,0.2870153,0.000628768],"study_design_scores_gemma":[0.0004468554,0.0001902146,0.4939339,0.00003439638,0.00001903459,0.00001325097,0.000108107,0.0001699292,0.000009652907,0.002000134,0.5026342,0.0004403953],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8338881,0.001127363,0.0004963982,0.001382421,0.002478098,0.0006288641,0.002056593,0.0001360134,0.1578062],"genre_scores_gemma":[0.9240039,0.01202922,0.00003225648,0.0002790004,0.0006061888,0.00005694975,0.0002269117,0.0001042889,0.06266126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2156189,"threshold_uncertainty_score":0.9999797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1308002427550408,"score_gpt":0.3217019618114176,"score_spread":0.1909017190563769,"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."}}