{"id":"W2924813464","doi":"","title":"Japan's ageing population points to our global future","year":2014,"lang":"en","type":"article","venue":"The New Scientist","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fell; Quarter (Canadian coin); Population ageing; Demography; Population; Economic stagnation; Population growth; Economic history; Demographic economics; History; Global population; Economics; Development economics; Geography; Socioeconomics; Political science; Sociology; Law; Archaeology; Cartography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002078936,0.0001181991,0.0001277008,0.00007420481,0.001255519,0.0004043435,0.0007345593,0.00005285699,0.00006084284],"category_scores_gemma":[0.000134817,0.0000937411,0.00009495585,0.001177822,0.00009396728,0.0002269408,0.0001381954,0.00008477585,0.0003704503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001302395,"about_ca_system_score_gemma":0.00003729783,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01383313,"about_ca_topic_score_gemma":0.03091018,"domain_scores_codex":[0.9978792,0.0002700494,0.0001850764,0.0003331929,0.0008720267,0.0004604397],"domain_scores_gemma":[0.9991997,0.00001697514,0.00009799414,0.0004142595,0.00006459106,0.0002064102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00002047772,0.00006492981,0.1963211,0.00001523658,0.00003443633,0.000006008274,0.006703523,0.000208553,0.00003964111,0.4486417,0.1815947,0.1663497],"study_design_scores_gemma":[0.000136547,0.00001346933,0.7490659,0.00001216362,0.00001693231,5.162753e-7,0.00149438,0.00004270616,0.000002978143,0.01128894,0.2377978,0.0001276098],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8483121,0.00006167814,0.002515577,0.03562169,0.00846469,0.0007245367,0.00001251554,0.0002214028,0.1040658],"genre_scores_gemma":[0.992249,0.000007053554,0.0008391285,0.001498073,0.001925287,0.000005865461,0.000005397897,0.000007585704,0.003462632],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5527448,"threshold_uncertainty_score":0.9927338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01065842590118497,"score_gpt":0.3073939961057574,"score_spread":0.2967355702045724,"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."}}