{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002355963,0.00008274547,0.00008621797,0.00007489868,0.0009551665,0.00005651903,0.0001998982,0.00005061903,0.00009610761],"category_scores_gemma":[0.0001093135,0.00008160272,0.00001326518,0.0008860462,0.001075339,0.0003044438,0.00007731269,0.00006968783,0.00004666709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007343261,"about_ca_system_score_gemma":0.00009205951,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05467489,"about_ca_topic_score_gemma":0.1291972,"domain_scores_codex":[0.9989853,0.00001875968,0.0000972043,0.0002517725,0.0002274124,0.0004195794],"domain_scores_gemma":[0.9996529,0.000008632123,0.00003116412,0.00004795444,0.00001263563,0.0002467751],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[8.938305e-7,0.000003726753,0.9663714,9.165139e-7,9.351861e-7,0.000002295036,0.02515026,2.772832e-7,0.003452841,0.002601186,0.001097285,0.001317943],"study_design_scores_gemma":[0.00005638229,0.00001412956,0.9918933,0.00000309399,0.000001364508,1.411662e-7,0.00148259,0.00003121014,0.0002162695,0.0001398101,0.006050772,0.0001109515],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8701203,0.00003034445,0.000001027342,0.0001066012,0.0001129773,0.00008184223,0.000005362105,0.00001052903,0.129531],"genre_scores_gemma":[0.9992945,0.000006038781,0.00001549976,0.0003833619,0.00009457276,0.000002084001,6.922215e-7,0.000004505989,0.0001987262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1293323,"threshold_uncertainty_score":0.9516201,"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."}}