{"id":"W2376249852","doi":"","title":"Adjustment and Countermeasure of Residence Area Southern Countryside in China","year":2002,"lang":"en","type":"article","venue":"Nongye xiandaihua yanjiu","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; Residence; China; Rural area; Quarter (Canadian coin); Geography; Residential area; Economic growth; Political science; Economics; Demographic economics; Civil engineering; Engineering","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":[0.0002497163,0.00008383855,0.0001525658,0.0004260846,0.0003360437,0.0004026429,0.0002221554,0.0001242481,0.001290044],"category_scores_gemma":[0.0009774296,0.00006434911,0.0001763322,0.0006833356,0.0003689968,0.0002107365,0.0004865088,0.0001886843,0.00007274562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009187838,"about_ca_system_score_gemma":0.0005200576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02422908,"about_ca_topic_score_gemma":0.02959326,"domain_scores_codex":[0.9997608,0.00005713314,0.00001253801,0.00006169281,0.00004000249,0.00006778441],"domain_scores_gemma":[0.9996357,0.00002370607,0.0001718006,0.00004071847,0.00007581234,0.00005221539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002354921,0.00004547906,0.9192703,0.00002293669,0.0000761018,0.0002721594,0.001173305,0.009176077,0.003264117,0.01503023,0.001781539,0.04965234],"study_design_scores_gemma":[0.000005968379,0.00005163998,0.9789937,0.000004114698,0.0000225356,0.00007310502,0.001290025,0.01316875,0.0007527189,0.002031656,0.00359586,0.000009938467],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997337,0.00004031316,0.0007681752,0.0001387721,0.000005421483,0.000003356293,0.00006137633,0.0000153077,0.001630234],"genre_scores_gemma":[0.9994123,0.00001191344,0.000128093,0.000007612083,0.000002714394,0.000001092955,0.00003530798,0.000001214661,0.0003996985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02422908,"threshold_uncertainty_score":0.04817611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02945696943698792,"score_gpt":0.1848390121483508,"score_spread":0.1553820427113629,"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."}}