{"id":"W2159224190","doi":"10.1061/9780784412435.084","title":"Population Forecast and Control in the Development of International New District: A Case Study on Fengdong New District in Xixian New Area","year":2012,"lang":"en","type":"article","venue":"","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Population; Control (management); Urban district; Population control; Value (mathematics); Computer science; Lake district; Geography; Operations research; Environmental planning; Engineering; Artificial intelligence; Sociology; Research methodology; Demography; Family planning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005696643,0.0002003821,0.0002084645,0.000475214,0.0009811934,0.0006625475,0.0005374948,0.0006162109,0.001307764],"category_scores_gemma":[0.001082304,0.0001268065,0.0003042296,0.0006108903,0.0006546894,0.0005685643,0.0005400602,0.0005090497,0.00006207079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002148247,"about_ca_system_score_gemma":0.001138836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08294845,"about_ca_topic_score_gemma":0.1253118,"domain_scores_codex":[0.9997199,0.0001005351,0.00000969364,0.00003567882,0.00004475985,0.00008936245],"domain_scores_gemma":[0.999617,0.0001779184,0.00005588475,0.0000228953,0.0000439187,0.00008228208],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003901475,0.001415569,0.727442,0.0001310768,0.0001055666,0.01833774,0.0168628,0.150655,0.001757853,0.01422006,0.002924575,0.06575773],"study_design_scores_gemma":[0.0001004601,0.001093798,0.5514529,0.00007778311,0.000159005,0.002080532,0.09218371,0.3304798,0.002674509,0.004470222,0.01508966,0.0001376057],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972969,0.000055766,0.0006494168,0.0001160632,0.000003859982,0.00001402376,0.00003142473,0.000003554802,0.0018291],"genre_scores_gemma":[0.998993,0.00006573064,0.0003385694,0.000004326497,0.000001998934,0.000007050042,0.00002751554,8.20532e-7,0.0005610056],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08294845,"threshold_uncertainty_score":0.1649312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0440275896978213,"score_gpt":0.2518479990157645,"score_spread":0.2078204093179432,"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."}}