{"id":"W2376345343","doi":"","title":"North Bay Economic Zone in Guangxi improve Cities lowest social security system's analysis","year":2010,"lang":"en","type":"article","venue":"The Journal of Guangxi Economic Management Cadre College","topic":"Regional Economic and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Countermeasure; Livelihood; Social security; Unemployment; Government (linguistics); Business; Bay; Economic growth; Geography; Economics; Market economy; Agriculture","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":[0.0001448907,0.000131334,0.0001262508,0.0009975899,0.000551215,0.0009473739,0.0002372249,0.0001352951,0.003484467],"category_scores_gemma":[0.0003206197,0.00008574484,0.0002117801,0.001642383,0.0003424739,0.0002986732,0.0007026112,0.0002330814,0.0001186752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002124911,"about_ca_system_score_gemma":0.001128417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1574356,"about_ca_topic_score_gemma":0.2102344,"domain_scores_codex":[0.999891,0.00001429858,0.000005994164,0.00002311008,0.00002055504,0.00004502178],"domain_scores_gemma":[0.9998747,0.00001466299,0.00003514412,0.00001008354,0.00003574126,0.00002965152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005225255,0.00002622686,0.9773325,0.00003775044,0.00004041505,0.0004753786,0.001595587,0.001324016,0.0003873602,0.008441574,0.002365792,0.007921196],"study_design_scores_gemma":[0.000003136101,0.000007234951,0.992804,0.00001075567,0.00001878896,0.00003707828,0.002428442,0.001631359,0.0001009823,0.0004966275,0.002457521,0.00000403466],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994457,0.0001087455,0.0001336089,0.0004421528,0.00000524931,0.000006753302,0.0004149434,0.000005839136,0.004425765],"genre_scores_gemma":[0.9984156,0.00006032955,0.00005948453,0.00001780454,0.000002607951,0.000003978581,0.0002771914,9.24601e-7,0.001162027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1574356,"threshold_uncertainty_score":0.3130384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008798254164593474,"score_gpt":0.1947557857636641,"score_spread":0.1859575315990706,"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."}}