{"id":"W2806208034","doi":"10.3968/10289","title":"Family Miniaturization and Its Influencing Factors in Urban China","year":2018,"lang":"en","type":"article","venue":"Canadian social science","topic":"Korean Urban and Social Studies","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Urbanization; China; Mainland China; Diversification (marketing strategy); Geography; Economic geography; Population; Economic growth; Social security; Demographic economics; Sustainable development; Socioeconomics; Period (music); Development economics; Demography; Sociology; Economics; Business; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005151412,0.0001625722,0.0001682888,0.0007642381,0.0009450071,0.000478186,0.0002572467,0.0001541295,0.001844596],"category_scores_gemma":[0.00138429,0.0001345987,0.0003183004,0.0009041809,0.0006415445,0.0003005333,0.0005600848,0.0002442535,0.00005755338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008904549,"about_ca_system_score_gemma":0.0008587934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04016829,"about_ca_topic_score_gemma":0.04711371,"domain_scores_codex":[0.9995641,0.0001233101,0.00004060783,0.00009044562,0.00007287152,0.0001085716],"domain_scores_gemma":[0.9991385,0.0001457817,0.0002891789,0.00007069441,0.0001165587,0.0002392483],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002825936,0.00001547086,0.9946519,0.000008926903,0.0000454559,0.0001860315,0.001593475,0.0001327827,0.0001453622,0.0002430824,0.0001153603,0.00283375],"study_design_scores_gemma":[7.157773e-7,0.00001110116,0.9980621,0.000004288259,0.000008801697,0.00005467968,0.001355754,0.0001888808,0.00002262657,0.00006236807,0.000225979,0.000002792582],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992281,0.00009312745,0.00003997386,0.00007376767,0.000002082997,0.000003722196,0.00003535268,0.000001672702,0.0005223341],"genre_scores_gemma":[0.9998319,0.00003586873,0.00001475389,0.000005356945,0.000001418642,0.000001497172,0.00002143367,5.007721e-7,0.00008715848],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04016829,"threshold_uncertainty_score":0.07986897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01027901771057639,"score_gpt":0.2124290668347957,"score_spread":0.2021500491242194,"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."}}