{"id":"W3172968524","doi":"10.1111/cjag.12294","title":"Learning from neighboring farmers: Does spatial dependence affect adoption of drought‐tolerant wheat varieties in China?","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Agricultural Economics/Revue canadienne d agroeconomie","topic":"Agricultural Innovations and Practices","field":"Agricultural and Biological Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Affect (linguistics); China; Agriculture; Business; Spillover effect; Ordered probit; Multivariate probit model; Probit model; Agricultural economics; Spatial analysis; Geography; Economics; Econometrics; Psychology; Microeconomics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003857877,0.0003051422,0.0006469581,0.00008999084,0.0002740322,0.000246307,0.0004144032,0.0001997827,0.000992984],"category_scores_gemma":[0.000171344,0.000137699,0.0002509764,0.0003673365,0.00008507096,0.001168743,0.00003953606,0.0005511367,0.00001027335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006856492,"about_ca_system_score_gemma":0.0002580516,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2247408,"about_ca_topic_score_gemma":0.9443779,"domain_scores_codex":[0.997802,0.0001451478,0.001026285,0.0003976356,0.00003499024,0.0005939919],"domain_scores_gemma":[0.9977553,0.0003287882,0.0009531658,0.00008549621,0.0003318454,0.0005453791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000428,0.0002725504,0.6251872,0.0001765078,0.001010937,0.0008472258,0.01186768,0.07440309,0.118686,0.01322479,0.0009441223,0.1529519],"study_design_scores_gemma":[0.0004195389,0.0003946913,0.9760724,0.0001761804,0.00006318729,0.0002623605,0.0125302,0.0002661512,0.003080948,0.00113605,0.005093039,0.0005052011],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948392,0.0003836256,0.000007280868,0.002898933,0.001014325,0.0001504466,0.0001338372,0.000007835286,0.0005645145],"genre_scores_gemma":[0.9980971,0.0002605023,0.0001639119,0.00008617558,0.0008596476,0.000006580092,0.0002541792,0.000003359052,0.0002685941],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7196372,"threshold_uncertainty_score":0.9999202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02133155352767337,"score_gpt":0.1787237923731059,"score_spread":0.1573922388454325,"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."}}