{"id":"W7113185159","doi":"","title":"A roma népesség számának prognózisa, a romák által felülreprezentált megyékben 2061-ig = Projection of Roma population in overrepresented counties until 2061","year":2020,"lang":"hu","type":"article","venue":"Repository of the Academy's Library (Library of the Hungarian Academy of Sciences)","topic":"Romani and Gypsy Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Population; Projection (relational algebra); Quarter (Canadian coin); Inequality; Population projection; Demographic analysis","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":[0.000224395,0.0003022608,0.0001737431,0.0005394835,0.0002555701,0.0007140056,0.0002650708,0.0002984793,0.02225421],"category_scores_gemma":[0.0004418337,0.000108614,0.000393858,0.0008722562,0.0001989479,0.0004186762,0.000682564,0.0003458867,0.004688095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005594139,"about_ca_system_score_gemma":0.00140879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03719973,"about_ca_topic_score_gemma":0.04967016,"domain_scores_codex":[0.9998918,0.00001902697,0.000007781398,0.00002680107,0.00002268332,0.00003195821],"domain_scores_gemma":[0.999871,0.00001492701,0.00004943139,0.00001086561,0.00003249097,0.0000211819],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007640744,0.0001305151,0.6835305,0.001270766,0.0004772619,0.001744807,0.00214245,0.006725396,0.004376865,0.01107419,0.08904645,0.1987167],"study_design_scores_gemma":[0.00007234029,0.0001089046,0.8125044,0.000447824,0.0001672219,0.00121632,0.003648054,0.002567925,0.001695904,0.001958419,0.1755694,0.00004332926],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7162166,0.005334472,0.005348965,0.01350795,0.0004273629,0.0002302263,0.1077455,0.0006579078,0.1505311],"genre_scores_gemma":[0.8795317,0.004614377,0.00351285,0.000433762,0.0001378587,0.0001493431,0.04393665,0.00007510379,0.06760827],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03719973,"threshold_uncertainty_score":0.07444769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05341672690463765,"score_gpt":0.3166830911554457,"score_spread":0.263266364250808,"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."}}