{"id":"W4387397514","doi":"10.1111/apv.12391","title":"How does the ‘Belt and Road Initiative’ change urbanisation patterns in Southeast Asia?","year":2023,"lang":"en","type":"article","venue":"Asia Pacific Viewpoint","topic":"Socioeconomic Development in Asia","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Montréal","funders":"Agence Nationale de la Recherche","keywords":"Urbanization; China; Economic geography; Southeast asia; Political science; Geography; Internationalization; Economy; Regional science; Economic growth; Development economics; Business; Sociology; International trade; Economics; Ethnology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001536434,0.0001611493,0.0002060653,0.0001388323,0.0004236909,0.0002283229,0.0002386051,0.000115736,0.0001404306],"category_scores_gemma":[0.000164582,0.0001137856,0.00005296003,0.0003250175,0.0002506674,0.0003803237,0.00008852189,0.0001955235,0.0002607265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001703008,"about_ca_system_score_gemma":0.00008570286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000578607,"about_ca_topic_score_gemma":0.002290104,"domain_scores_codex":[0.998323,0.0004043935,0.0002403916,0.0003332442,0.0002733907,0.0004255456],"domain_scores_gemma":[0.9993506,0.0001741609,0.000143626,0.0002081822,0.00003537707,0.00008806297],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001450323,0.00003637537,0.2149901,0.00005847552,0.00006401064,0.00002892,0.5160061,3.850341e-7,0.00005563834,0.06257471,0.00332769,0.2028431],"study_design_scores_gemma":[0.0002419317,0.00001392386,0.4546551,0.00005517893,0.00000780834,0.000001526326,0.4947565,0.00003721539,0.0000251763,0.005154999,0.04484389,0.0002068485],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6467382,0.000360953,0.0000430334,0.2603215,0.001809193,0.002090605,0.00007142156,0.0003971089,0.08816794],"genre_scores_gemma":[0.99679,0.0006850113,0.00004266372,0.0002068774,0.0002970883,0.0002822159,0.00002738326,0.00001998475,0.001648813],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3500517,"threshold_uncertainty_score":0.4640043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06302487779786105,"score_gpt":0.2916556148599606,"score_spread":0.2286307370620996,"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."}}