{"id":"W4398330871","doi":"10.7910/dvn/o7eggp/zshq5y","title":"childmarr_3Oct2019-1.tab","year":2019,"lang":"de","type":"dataset","venue":"Harvard Dataverse","topic":"Demographic Trends and Gender Preferences","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Statistics; Geography; Demography; Genealogy; Mathematics; History; Sociology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001037857,0.002080411,0.001394331,0.003777528,0.000807327,0.002868929,0.002757674,0.001943761,0.2011222],"category_scores_gemma":[0.006359965,0.0008995167,0.001281093,0.007169727,0.0004340887,0.001506628,0.002199016,0.00160728,0.2143888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001585302,"about_ca_system_score_gemma":0.002073841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03064348,"about_ca_topic_score_gemma":0.04830757,"domain_scores_codex":[0.9991581,0.0001342797,0.0001072488,0.0002358769,0.0001687447,0.0001957661],"domain_scores_gemma":[0.9977759,0.000616575,0.0002756103,0.0005286966,0.0004707853,0.0003324723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002616757,0.000007997585,0.0004427933,0.0002410218,0.00001243748,0.000006702043,0.00001179156,0.0000898014,0.0000319054,0.000239404,0.9979511,0.0009389555],"study_design_scores_gemma":[0.0002697602,0.00001987078,0.004445382,0.0002794137,0.00002418088,0.00003916987,0.00008017185,0.000320233,0.0002384267,0.0009349921,0.9933194,0.00002899708],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004633019,0.00002355862,0.00001852272,0.00004005042,0.00001476788,0.000003081161,0.9993218,0.0001609333,0.0003709852],"genre_scores_gemma":[0.0003274566,0.00004458737,0.0001057006,0.00004763555,0.00001063483,0.00004617845,0.9983723,0.00008786252,0.0009577628],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7988778,"threshold_uncertainty_score":0.6728207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03715946658548194,"score_gpt":0.2863756100924306,"score_spread":0.2492161435069486,"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."}}