{"id":"W6978011165","doi":"10.7298/8943-wa03","title":"Heterogeneous Choice in WTP and WTA for land rental arrangement in Rural China: Choice experiment from the Field","year":2019,"lang":"en","type":"article","venue":"eCommons (Cornell University)","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Waterloo; Central University of Finance and Economics; Nanjing Agricultural University; Zhejiang University; Higher Education Discipline Innovation Project; Government of Jiangsu Province","keywords":"Field (mathematics); Renting; Rental housing; Land use; Willingness to pay","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001207491,0.00009970873,0.0001807532,0.00008585901,0.00004723927,0.00002213893,0.000161488,0.00005756488,0.0003937736],"category_scores_gemma":[0.00001263267,0.0001105894,0.00004980353,0.00006756443,0.00002046879,0.0001495434,0.00009580381,0.00008651196,0.00008967469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001995084,"about_ca_system_score_gemma":0.000003450002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005166031,"about_ca_topic_score_gemma":0.005306034,"domain_scores_codex":[0.9993597,0.00001636084,0.0001868347,0.00026563,0.000010924,0.0001605199],"domain_scores_gemma":[0.9995033,0.0001718341,0.00009228881,0.000198472,0.000001398568,0.0000327757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002141366,0.00005728806,0.9962263,0.000003647181,0.00001593243,9.763468e-7,0.0002499667,0.002305606,0.00001555439,0.0008100832,0.0001246412,0.0001685662],"study_design_scores_gemma":[0.001796418,0.00008144968,0.9827796,0.00001325525,0.000004446225,3.650827e-7,0.0002663791,0.008628516,0.0000785714,0.0008237516,0.005372075,0.000155184],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961469,0.0003668058,0.000132972,0.0002926057,0.0001716049,0.0003652003,0.00006605553,0.000006639598,0.00245121],"genre_scores_gemma":[0.9990773,0.000108363,0.0000430302,0.000169601,0.00003572843,0.000004816231,0.00003321933,0.000008890138,0.000519106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01344674,"threshold_uncertainty_score":0.7809529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0513099664612793,"score_gpt":0.1935299355635068,"score_spread":0.1422199691022275,"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."}}