{"id":"W2036931007","doi":"10.5539/enrr.v5n1p22","title":"Predicting Greenhouse Gas Reduction and Profit Analysis by Soil Carbon Sequestration in Corn Field with Different Application Rates of Biochar during Cultivation Periods","year":2015,"lang":"en","type":"article","venue":"Environment and Natural Resources Research","topic":"Soil Carbon and Nitrogen Dynamics","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biochar; Greenhouse gas; Carbon sequestration; Environmental science; Agronomy; Carbon dioxide; Chemistry; Waste management; Ecology; Engineering; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.0002974202,0.00008731836,0.0001221628,0.00006170499,0.00007675996,0.00003286621,0.00005548255,0.00007225922,0.00000684394],"category_scores_gemma":[0.00002886886,0.00003912012,0.00001789247,0.0003171171,0.00009957959,0.00006888727,0.000050961,0.0001827724,1.712452e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005691777,"about_ca_system_score_gemma":0.00000249095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001848785,"about_ca_topic_score_gemma":0.0007639566,"domain_scores_codex":[0.9989774,0.000118502,0.0001446354,0.0002448332,0.0003578958,0.0001567153],"domain_scores_gemma":[0.9997287,0.00006835246,0.00006442507,0.00004408241,0.00002684119,0.00006763751],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001778164,0.00002263227,0.70776,0.000007917326,0.00001673415,3.91163e-7,0.0003703881,0.00002951828,0.2871836,0.000001865422,8.134689e-7,0.004428291],"study_design_scores_gemma":[0.0002708574,0.0004325544,0.8790334,0.00001596688,0.00002222248,0.000002145799,0.0015732,0.01974439,0.09877125,0.00002696611,0.00001048867,0.00009656225],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989083,0.0005440314,8.480915e-7,0.0002668746,0.000005128489,0.0002345819,0.000003125259,0.00001050278,0.00002662224],"genre_scores_gemma":[0.9993834,0.0003930744,0.0000089095,0.000002203784,0.00003688316,0.00002917341,0.00006228385,0.000001254352,0.00008274838],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1884123,"threshold_uncertainty_score":0.2794822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02056348669751889,"score_gpt":0.2570170966512217,"score_spread":0.2364536099537028,"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."}}