{"id":"W3118648417","doi":"10.3390/land10010058","title":"Tracing Agricultural Land Transfer in China: Some Legal and Policy Issues","year":2021,"lang":"en","type":"article","venue":"Land","topic":"China's Socioeconomic Reforms and Governance","field":"Social Sciences","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Peasant; Agrarian society; China; Land tenure; Restructuring; Agricultural land; Context (archaeology); Land management; Land law; Agriculture; Business; Economic growth; Natural resource economics; Economics; Economic system; Geography; Political science; Law; Finance","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":[0.0001217329,0.00006397958,0.0001326904,0.00001515331,0.0001450258,0.0001051131,0.00005213324,0.00005823115,0.00003907192],"category_scores_gemma":[0.0000280856,0.00004542726,0.00003179814,0.00008231988,0.00005620761,0.0003528894,0.00001252669,0.00009313678,0.00000518866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006482015,"about_ca_system_score_gemma":0.00008078531,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07750855,"about_ca_topic_score_gemma":0.149767,"domain_scores_codex":[0.9994619,0.00003149745,0.00009934129,0.00013724,0.00008084244,0.0001891712],"domain_scores_gemma":[0.9998574,0.00001745979,0.0000143853,0.00004752505,0.00000895482,0.00005422247],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001620072,0.00006412841,0.8545014,0.00003783817,0.0000240519,0.00006102839,0.07326785,0.00002876231,0.0003184739,0.06340677,0.0003655907,0.007907918],"study_design_scores_gemma":[0.0004747717,0.000009754223,0.9687336,0.00002271657,0.000003115979,0.000005994446,0.001171281,0.000005952329,0.0001351283,0.003130103,0.02619806,0.0001095015],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9805456,0.001209846,0.000001420337,0.009616302,0.0000874266,0.00005253287,0.00001000371,0.00001394846,0.008462924],"genre_scores_gemma":[0.9925042,0.001046628,0.0000167082,0.0001443579,0.0005709556,0.000002418877,0.000003367079,0.000003645437,0.005707681],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1142322,"threshold_uncertainty_score":0.9286344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006890454967917975,"score_gpt":0.267478018313494,"score_spread":0.260587563345576,"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."}}