{"id":"W1934533906","doi":"10.25336/p6z614","title":"Demographic Relationships at the Macro Level","year":2008,"lang":"en","type":"article","venue":"Canadian Studies in Population","topic":"Gender, Labor, and Family Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Macro; Census; Macro level; Regression analysis; Econometrics; Regression; Population; Fertility; Focus (optics); Statistics; Geography; Demography; Mathematics; Sociology; Computer science; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0005228285,0.00007521042,0.00009737758,0.0001614032,0.002625413,0.0000109826,0.0001187819,0.00008722345,0.00001670316],"category_scores_gemma":[0.0004599316,0.00006607739,0.00003487142,0.0006540946,0.0003828793,0.00009392933,0.00001981387,0.0001401837,0.00001957577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008190417,"about_ca_system_score_gemma":0.0001646087,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3251482,"about_ca_topic_score_gemma":0.9898947,"domain_scores_codex":[0.9989927,0.0002025217,0.00017109,0.0001459224,0.0001827525,0.0003049681],"domain_scores_gemma":[0.9994712,0.0001453428,0.00004741033,0.0001426225,0.0000824329,0.0001109712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[8.121682e-7,0.000002175386,0.9589393,0.000001859312,0.00001028208,0.000005941158,0.02476098,0.0001339294,2.583309e-7,0.01288052,0.00303429,0.0002296711],"study_design_scores_gemma":[0.00007478302,0.000002744942,0.9700074,0.000006585355,0.000006383603,0.00000188975,0.01684186,0.00005345719,6.169449e-8,0.004040104,0.008881344,0.00008334302],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9865535,0.001575908,0.00001456156,0.001570847,0.0006588878,0.0002042897,0.00002252837,0.00002040253,0.009379067],"genre_scores_gemma":[0.9958755,0.0009454372,0.00008248672,0.0002969213,0.0001149056,0.00001729747,0.00002492472,0.000007243801,0.002635293],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6647466,"threshold_uncertainty_score":0.998673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1730461685212868,"score_gpt":0.3313635002190186,"score_spread":0.1583173316977317,"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."}}