{"id":"W4292616212","doi":"10.31235/osf.io/87acb","title":"From bust to boom? Birth and fertility responses to the COVID-19 pandemic","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Max-Planck-Institut für demografische Forschung","keywords":"Fertility; Pandemic; Bust; Birth rate; Demography; Baby boom; Sub-replacement fertility; Total fertility rate; Geography; Recession; Coronavirus disease 2019 (COVID-19); Economics; Boom; Population; Medicine; Family planning; Research methodology; Sociology","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":[0.0008440273,0.0001042975,0.0002363949,0.0004858503,0.0002538745,0.0008143178,0.0002003559,0.0004240232,0.001933887],"category_scores_gemma":[0.003014207,0.0001244003,0.0003037624,0.0005835068,0.0003460624,0.000322454,0.0006146948,0.0006114044,0.0001997682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004686493,"about_ca_system_score_gemma":0.0003168774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01887272,"about_ca_topic_score_gemma":0.01756918,"domain_scores_codex":[0.9997811,0.00007459745,0.000009863136,0.00003796275,0.00002286565,0.00007364733],"domain_scores_gemma":[0.9992775,0.0002008334,0.0002730608,0.00004376633,0.00008115843,0.0001236726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003439834,0.00006538202,0.9692095,0.00007555239,0.0001324017,0.0003389608,0.000954697,0.004552551,0.0007694486,0.002332247,0.004326191,0.01689898],"study_design_scores_gemma":[0.000004105754,0.00005567413,0.9952988,0.0000236191,0.0000150943,0.00006170115,0.00128865,0.001296981,0.0001403592,0.000297626,0.001508906,0.0000085776],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946073,0.0004460645,0.0001627582,0.0008570329,0.00002616159,0.000007114344,0.0021626,0.0000108965,0.001720217],"genre_scores_gemma":[0.9978639,0.0003073927,0.0001028313,0.0001301108,0.00002405313,0.000005106901,0.001189527,0.000004828164,0.000372343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01887272,"threshold_uncertainty_score":0.03752577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09775948917808458,"score_gpt":0.3890364455560522,"score_spread":0.2912769563779676,"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."}}