{"id":"W6957553572","doi":"10.6068/dp14ba868a17272","title":"Trend 2000 - 2011. Statistics Canada. CANSIM: Income, Pensions, Spending and Wealth - Household, Family and Personal Income | Country: Canada | Table: Family characteristics, by family type, age of older adult, and family income | Variable: 25 to 34 years, Lone-parent families, $60,000 and over | Units: #, 2000-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-119.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Personal income; Census; Socioeconomic status; Demographic statistics; Economic statistics; Official statistics; Family income; Population; Household income; Summary statistics","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":[0.002222174,0.002421344,0.002853691,0.007787412,0.003204498,0.00478415,0.00570994,0.001520923,0.08535473],"category_scores_gemma":[0.01962732,0.001832163,0.002348177,0.0375202,0.0006110918,0.002551628,0.002550489,0.003404097,0.05012949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04919431,"about_ca_system_score_gemma":0.1097384,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9935409,"about_ca_topic_score_gemma":0.9920879,"domain_scores_codex":[0.9962903,0.0002592805,0.0004585352,0.0004937078,0.001636195,0.0008618683],"domain_scores_gemma":[0.9690546,0.00126567,0.001015688,0.00102455,0.02616285,0.001476688],"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":[0.00002624145,0.000006055257,0.001091946,0.0002723931,0.00002299955,0.000006433934,0.00002331438,0.0001037493,0.000007560984,0.0003536633,0.9965004,0.001585348],"study_design_scores_gemma":[0.0002017598,0.00001351764,0.02887259,0.001124922,0.00008293688,0.00003281336,0.0004831239,0.0005515745,0.0001799129,0.0008331737,0.9675153,0.0001084215],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004684808,0.00004256183,0.00002006137,0.00009568854,0.00001927446,0.00001302044,0.9991104,0.00005105579,0.000601102],"genre_scores_gemma":[0.0006658025,0.0002263957,0.0003195749,0.0001197182,0.00001321511,0.0001241708,0.9957258,0.00008700905,0.002718416],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08535473,"threshold_uncertainty_score":0.3569314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02018189596481584,"score_gpt":0.2468726670496907,"score_spread":0.2266907710848749,"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."}}