{"id":"W1972663001","doi":"10.4018/ijabim.2013100105","title":"An Empirical Study on China’s Regional Carbon Emissions of Agriculture","year":2013,"lang":"en","type":"article","venue":"International Journal of Asian Business and Information Management","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Agriculture; China; Greenhouse gas; Carbon fibers; Environmental science; Natural resource economics; Agricultural economics; Environmental protection; Economics; Geography; Ecology","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":[0.000853079,0.000253458,0.0002608757,0.001215303,0.0004350652,0.0006613822,0.0004204476,0.0003014173,0.001742272],"category_scores_gemma":[0.002285808,0.0001379869,0.000539052,0.003359258,0.0004074146,0.0006885453,0.0004207314,0.0004755543,0.0001642006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001748278,"about_ca_system_score_gemma":0.001280865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07521436,"about_ca_topic_score_gemma":0.1057614,"domain_scores_codex":[0.9996172,0.00008853607,0.00002844738,0.00006758762,0.00009396132,0.0001041187],"domain_scores_gemma":[0.9970926,0.001436846,0.0006321368,0.0001180358,0.0004955109,0.0002248063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005002887,0.00009775878,0.9866489,0.00006361783,0.0001349667,0.0005301486,0.0007500764,0.004962056,0.0004913692,0.0008234679,0.0007126439,0.004734988],"study_design_scores_gemma":[0.000006406707,0.00003937878,0.9915474,0.00001281511,0.00004936988,0.00007172904,0.001715949,0.005241662,0.0003178357,0.0001151829,0.0008735661,0.000008780915],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980762,0.0001280149,0.00006897086,0.0000860264,0.000002170741,0.000004894571,0.0002617206,0.000003475448,0.001368644],"genre_scores_gemma":[0.9991823,0.0001233627,0.00005600522,0.00001661815,0.000002779378,0.000003665772,0.0004115065,9.911984e-7,0.0002028846],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07521436,"threshold_uncertainty_score":0.1495531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006483994211668856,"score_gpt":0.256976637048742,"score_spread":0.2504926428370732,"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."}}