{"id":"W2560556739","doi":"10.1016/j.jenvman.2016.11.080","title":"Environmental impacts and production performances of organic agriculture in China: A monetary valuation","year":2016,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Organic Food and Agriculture","field":"Agricultural and Biological Sciences","cited_by":98,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Biotechnology and Biological Sciences Research Council; National Natural Science Foundation of China","keywords":"Production (economics); Contingent valuation; China; Valuation (finance); Natural resource economics; Agriculture; Environmental science; Organic farming; Economics; Agricultural economics; Environmental protection; Willingness to pay; Geography; Macroeconomics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001913831,0.0007554344,0.0004687146,0.002273764,0.000706645,0.002132975,0.0008369305,0.0008909208,0.001667978],"category_scores_gemma":[0.002738335,0.0004129089,0.0008710485,0.002898364,0.001481773,0.002115635,0.001239979,0.0004933876,0.00009143931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005751869,"about_ca_system_score_gemma":0.001840153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03218505,"about_ca_topic_score_gemma":0.0266524,"domain_scores_codex":[0.9991146,0.0002977544,0.00005570506,0.0001128328,0.0001641199,0.0002549457],"domain_scores_gemma":[0.9981415,0.0006539784,0.0006053615,0.00009607301,0.0002315171,0.000271487],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001869553,0.0005843616,0.7235637,0.0001994269,0.0008088672,0.003493387,0.001175015,0.2198015,0.003845948,0.01501804,0.001360632,0.0282797],"study_design_scores_gemma":[0.0001474008,0.0006345408,0.6693407,0.00004758445,0.0007251661,0.0002745422,0.002980748,0.3139309,0.001084197,0.009500578,0.001205293,0.0001283238],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983515,0.0001442333,0.00030564,0.0001259077,0.000004178241,0.000008375673,0.0001026817,0.00000339999,0.000954145],"genre_scores_gemma":[0.999615,0.00007047381,0.00004359096,0.000004900439,0.000005030193,0.000003216368,0.00005788903,6.483801e-7,0.0001992534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03218505,"threshold_uncertainty_score":0.06399542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004294385319436385,"score_gpt":0.15607185611938,"score_spread":0.1517774707999436,"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."}}