{"id":"W4399281579","doi":"10.1016/j.jeca.2024.e00368","title":"Asymmetric effects between economic development and fertility: What do 140 years of data tell us?","year":2024,"lang":"en","type":"article","venue":"The Journal of Economic Asymmetries","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Fertility; Economics; Demography; Sociology; Population","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0154649,0.000472778,0.001734944,0.003313223,0.0005647457,0.00355475,0.001359227,0.001973811,0.006001394],"category_scores_gemma":[0.0687286,0.0007661697,0.001657255,0.006188117,0.002209919,0.007958652,0.002976843,0.003860401,0.001939189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00109291,"about_ca_system_score_gemma":0.002459735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01780372,"about_ca_topic_score_gemma":0.02041927,"domain_scores_codex":[0.9945926,0.001683627,0.001160774,0.0008473819,0.001107342,0.0006081703],"domain_scores_gemma":[0.8530404,0.0867177,0.02972984,0.01650729,0.009739471,0.004265228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007653802,0.0001913411,0.8266557,0.001851817,0.004600795,0.0002956174,0.001361039,0.001244978,0.0003763629,0.009597827,0.04643326,0.1066259],"study_design_scores_gemma":[0.00008185317,0.0001515562,0.8739882,0.003003662,0.001517102,0.0004622435,0.002513758,0.0005782779,0.0004547808,0.01605832,0.1010498,0.0001404507],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5400976,0.2278784,0.008922868,0.102601,0.003419159,0.0001058245,0.09212593,0.0002083349,0.02464094],"genre_scores_gemma":[0.8863381,0.0535433,0.002919261,0.01923409,0.002813851,0.0001214428,0.03292908,0.0002119014,0.001889098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01780372,"threshold_uncertainty_score":0.08178717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04631244367837835,"score_gpt":0.2534310328720184,"score_spread":0.2071185891936401,"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."}}