{"id":"W142522410","doi":"","title":"The Northern America Fertility Divide","year":2005,"lang":"en","type":"article","venue":"Policy review","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Population; Fertility; Geography; Government (linguistics); Total fertility rate; Development economics; Political science; Demographic economics; Economic growth; Demography; Economics; Sociology; Family planning; Law","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":[0.0006896996,0.0003065606,0.0002884936,0.001721129,0.004772728,0.003099706,0.0008664391,0.0006827209,0.07335456],"category_scores_gemma":[0.001783746,0.0001322855,0.0001992052,0.002075131,0.00101473,0.001276975,0.00215451,0.001751549,0.0107293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009794886,"about_ca_system_score_gemma":0.01096661,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3928179,"about_ca_topic_score_gemma":0.5285771,"domain_scores_codex":[0.9991176,0.00007453571,0.00001677577,0.0001230163,0.0002513319,0.0004168046],"domain_scores_gemma":[0.9993229,0.00005261412,0.00005371989,0.00003423516,0.000253042,0.0002835371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00005044833,0.00004402415,0.01722288,0.0001191671,0.00001323554,0.0003494282,0.004780982,0.00008774774,0.000209004,0.1362369,0.6607649,0.1801212],"study_design_scores_gemma":[0.000004257696,0.000005001552,0.02052312,0.00008472621,0.000002568227,0.00007361464,0.001227058,0.00002344378,0.00003841993,0.001371044,0.976642,0.000004742656],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02088091,0.01587319,0.0003127825,0.03196125,0.001186662,0.00006459749,0.009730779,0.0001992092,0.9197905],"genre_scores_gemma":[0.3003017,0.02145295,0.0009296854,0.02124014,0.002271756,0.0003320309,0.01330838,0.0002130807,0.6399503],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6071821,"threshold_uncertainty_score":0.7810629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02761033406886777,"score_gpt":0.3666847371423422,"score_spread":0.3390744030734745,"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."}}