{"id":"W7098393059","doi":"","title":"is given to the source. Why are Saving Rates of Urban Households in China Rising?","year":2008,"lang":"en","type":"article","venue":"","topic":"Plant and Biological Electrophysiology Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Consumption (sociology); Consumption smoothing; China; Quarter (Canadian coin); Household income; Private consumption; Permanent income hypothesis","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":[0.0009583246,0.0005294462,0.000870737,0.005014341,0.0005553568,0.001611306,0.001311364,0.001246084,0.2165195],"category_scores_gemma":[0.007443263,0.0002590374,0.0004009708,0.008325461,0.0003621391,0.001200882,0.001059648,0.0008767212,0.0460002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002712505,"about_ca_system_score_gemma":0.001834198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08716697,"about_ca_topic_score_gemma":0.03209882,"domain_scores_codex":[0.9993992,0.00004882122,0.00007423545,0.00009451405,0.0002315112,0.0001517959],"domain_scores_gemma":[0.9967368,0.0003973598,0.0007157475,0.0001442728,0.001699964,0.0003057711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001525358,0.00001539916,0.03111852,0.0005912541,0.00003324661,0.0002679141,0.0002429876,0.0008010153,0.0001833046,0.007725319,0.8951855,0.06368293],"study_design_scores_gemma":[0.0003362604,0.0000757876,0.2752045,0.000722035,0.00008480583,0.0005067415,0.001325353,0.005149865,0.0009311642,0.004187148,0.7113771,0.00009917435],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.06366911,0.007035795,0.002033036,0.08009675,0.007175238,0.000527779,0.7011117,0.002943635,0.1354069],"genre_scores_gemma":[0.4208081,0.01230693,0.001501332,0.004336616,0.002382534,0.00094313,0.2133691,0.0006546548,0.3436976],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2165195,"threshold_uncertainty_score":0.7243298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03153963369653825,"score_gpt":0.2156289726883552,"score_spread":0.1840893389918169,"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."}}