{"id":"W2227303409","doi":"","title":"Industrial Transformation and Low-Carbon Development of Resource-Based Cities: Taking Ordos City as an Example","year":2016,"lang":"en","type":"article","venue":"Studies in sociology of science","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Resource (disambiguation); Business; Investment (military); Sustainable development; Industrial city; Pollution; Environmental pollution; Natural resource economics; Environmental economics; Secondary sector of the economy; Economy; Environmental science; Environmental protection; Economic geography; Economics; Computer science; Industrial zone; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009902592,0.0001556898,0.0001250958,0.0007840112,0.0008017867,0.001576882,0.0001962607,0.0002975781,0.001798841],"category_scores_gemma":[0.0001884593,0.00006083479,0.0002797761,0.002664569,0.0005653465,0.0005756162,0.000671022,0.0002825532,0.00009013588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002234878,"about_ca_system_score_gemma":0.001178793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1032316,"about_ca_topic_score_gemma":0.1978944,"domain_scores_codex":[0.9999242,0.00001999672,0.000002257644,0.000007606363,0.00001222494,0.0000336203],"domain_scores_gemma":[0.9998742,0.00002371908,0.00003135547,0.000007197616,0.00003060351,0.00003282288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003551251,0.001073509,0.5552607,0.0002491048,0.0001273576,0.007388662,0.00685118,0.05957874,0.003185145,0.3047879,0.005942791,0.05519984],"study_design_scores_gemma":[0.0001174547,0.0001685129,0.7230094,0.00008039349,0.0001591576,0.0006590656,0.04270157,0.1213614,0.00259413,0.06549687,0.04356878,0.00008329956],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.971957,0.0003657165,0.0009550369,0.0006172518,0.000008998304,0.00001682516,0.0001283214,0.00001248008,0.02593828],"genre_scores_gemma":[0.9979473,0.0002715093,0.0003004864,0.00001449411,0.000002856644,0.000004031353,0.00007176627,0.000002041744,0.001385562],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1032316,"threshold_uncertainty_score":0.2052613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1473040672909547,"score_gpt":0.2826577980617395,"score_spread":0.1353537307707848,"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."}}