{"id":"W4327967413","doi":"10.54691/bcpbm.v41i.4434","title":"Exploring Left Behind Children in China","year":2023,"lang":"en","type":"article","venue":"BCP Business & Management","topic":"China's Socioeconomic Reforms and Governance","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"China; Urbanization; Left behind; Rural area; Economic growth; Distribution (mathematics); Resource (disambiguation); Geography; Sociology; Socioeconomics; Psychology; Political science; Mental health","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":[0.0005404461,0.0001200206,0.0001564508,0.0001447377,0.0002811801,0.00007572372,0.0003296114,0.00003604605,0.0001179935],"category_scores_gemma":[0.00002371869,0.0001152312,0.00004840516,0.0003482246,0.00007070268,0.0006023435,0.0001908507,0.0000847702,0.0003395113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002304984,"about_ca_system_score_gemma":0.0000347723,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01186593,"about_ca_topic_score_gemma":0.005752573,"domain_scores_codex":[0.998801,0.00002621096,0.000204586,0.0002894057,0.0002620438,0.0004167496],"domain_scores_gemma":[0.9996235,0.00001312211,0.00007892225,0.0002159514,0.00001651653,0.0000519772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00001528852,0.0001082748,0.06658056,0.00007581923,0.00006312397,0.00006661488,0.02922127,0.001743078,0.000003665292,0.01293052,0.00441778,0.884774],"study_design_scores_gemma":[0.0002767928,7.191177e-7,0.953147,0.0000405018,0.000005764868,2.3468e-7,0.0009471562,0.00001475161,0.000002247208,0.003091358,0.04232447,0.0001490103],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9797798,0.00005280449,0.000006615702,0.004191471,0.0005582093,0.0003628545,0.000003868737,0.0001417922,0.01490259],"genre_scores_gemma":[0.9867477,0.002884749,0.00007246395,0.00008372246,0.0002802856,0.00005703868,0.00001332201,0.00001803791,0.00984263],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8865665,"threshold_uncertainty_score":0.9947141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04324925210733681,"score_gpt":0.2718944079667556,"score_spread":0.2286451558594187,"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."}}