{"id":"W1761036810","doi":"10.3968/j.sss.1923018420110202.4z393","title":"Analysis of Income Urban-Rural Gap of Guizhou Province in the Condition of Dualization","year":2011,"lang":"en","type":"article","venue":"Studies in sociology of science","topic":"Regional Economic and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Net income; Socioeconomics; Low income; Geography; Household income; Rural area; Net national income; Economics; Demographic economics; Political science; Public economics; Gross income","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001676547,0.0000585302,0.0006094406,0.0006266797,0.0000381932,6.256394e-7,0.0003476949,0.0000443915,0.00003013561],"category_scores_gemma":[0.0002928576,0.00004862526,0.000107089,0.001020224,0.01080517,0.000123725,0.00007233967,0.00004638969,0.000001032323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005085783,"about_ca_system_score_gemma":0.00003558433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009079687,"about_ca_topic_score_gemma":0.0003118562,"domain_scores_codex":[0.998828,0.000037988,0.0008115544,0.0001675241,0.00004387615,0.0001110592],"domain_scores_gemma":[0.9986864,0.000148298,0.0008835751,0.000174385,0.00009911074,0.000008169093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009805182,0.00005726176,0.7801077,0.00002619376,0.0001584385,1.864905e-7,0.03453507,0.0005630979,0.00004276973,0.1844599,0.00001288687,0.00002666913],"study_design_scores_gemma":[0.0002007459,0.0001080165,0.9190121,0.00001872082,0.00005341315,1.597725e-7,0.02833393,0.002755544,0.0002060854,0.04923591,0.000006779132,0.00006861667],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960498,0.001161883,0.0002148163,0.00008884513,0.00005967319,0.00007665841,0.00003106081,9.892776e-7,0.002316232],"genre_scores_gemma":[0.9992505,0.0005477643,0.0001423108,0.00002526778,0.000005099789,0.000006468787,0.000003057005,0.000001401729,0.00001812674],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1389043,"threshold_uncertainty_score":0.9918869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1266399822649879,"score_gpt":0.3182163791533604,"score_spread":0.1915763968883725,"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."}}