{"id":"W1492385259","doi":"10.1787/880242325663","title":"Trends and Determinants of Fertility Rates","year":2005,"lang":"en","type":"report","venue":"OECD social employment and migration working papers","topic":"Gender, Labor, and Family Dynamics","field":"Social Sciences","cited_by":189,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Università degli Studi di Torino; York University","keywords":"Fertility; Total fertility rate; Economics; Macro; Demographic economics; Developing country; Development economics; Demography; Economic growth; Population; Sociology; Family planning; Research methodology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008991643,0.0002466615,0.00046185,0.0001503901,0.0008046844,0.0001222173,0.0001234107,0.0004677037,0.00009841662],"category_scores_gemma":[0.00005670126,0.0002490706,0.0001345452,0.0001728515,0.0004053291,0.0000712239,0.00004820669,0.0001887112,0.000001482883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002053269,"about_ca_system_score_gemma":0.0004826587,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004519523,"about_ca_topic_score_gemma":0.06257821,"domain_scores_codex":[0.9979603,0.000163249,0.0004433282,0.0003633396,0.0007417283,0.0003280789],"domain_scores_gemma":[0.9992077,0.00008153539,0.0003784933,0.0001028806,0.0001211114,0.0001082264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002208215,0.00006040207,0.5986768,0.00005992882,0.00007133694,0.000002075096,0.03432074,7.022532e-7,0.00007481001,0.0003595634,0.001334955,0.3650166],"study_design_scores_gemma":[0.0002466245,0.0000302049,0.6796135,0.00008222833,0.000151072,5.676493e-7,0.00628673,0.00001164871,0.000009355827,0.00008584208,0.3131459,0.0003364037],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8556304,0.002229189,0.00000314298,0.0006867145,0.0008943771,0.0002598155,0.00004110183,0.00007105935,0.1401842],"genre_scores_gemma":[0.9708352,0.01014326,0.00005902266,0.00007523035,0.0006431815,0.00001802993,0.00006258722,0.00002389221,0.01813961],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3646802,"threshold_uncertainty_score":0.9999961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05432567056255388,"score_gpt":0.3451275265958075,"score_spread":0.2908018560332536,"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."}}