{"id":"W4409874957","doi":"10.1016/j.agsy.2025.104361","title":"Harmonizing soil carbon simulation models, emission factors and direct measurements used in LCA of agricultural systems","year":2025,"lang":"en","type":"article","venue":"Agricultural Systems","topic":"Agriculture Sustainability and Environmental Impact","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"HORIZON EUROPE Food, Bioeconomy, Natural Resources, Agriculture and Environment; Horizon 2020; European Commission","keywords":"Agriculture; Environmental science; Carbon fibers; Soil carbon; Soil science; Agricultural engineering; Computer science; Soil water; Engineering; Ecology; Algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003365833,0.0003698384,0.0005122035,0.00005392756,0.0001614728,0.00008846549,0.0001967409,0.0002163683,0.00000615612],"category_scores_gemma":[0.00004807402,0.000197058,0.00009533694,0.0005651754,0.00009611953,0.000594168,0.0001761451,0.000182358,0.000002891482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001066683,"about_ca_system_score_gemma":0.000008155136,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01228215,"about_ca_topic_score_gemma":0.0002526223,"domain_scores_codex":[0.9976278,0.000250359,0.0006240574,0.0005068266,0.0005713428,0.0004196339],"domain_scores_gemma":[0.9992908,0.0001050849,0.0002447551,0.0001870839,0.00002844425,0.0001437983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001392539,0.00009589359,0.5378605,0.0001511307,0.00003428412,0.000001180189,0.0007605531,0.3813047,0.07951427,0.00001112032,0.000153776,0.00009865203],"study_design_scores_gemma":[0.0004635203,0.00005648882,0.973054,0.0002921716,0.00004688194,0.000003933096,0.0088946,0.01324023,0.003538112,0.00001291589,0.00007775224,0.0003193856],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908744,0.0006359004,0.00001750458,0.00005472747,0.0003085222,0.0009834362,0.000008702728,0.00005591245,0.00706095],"genre_scores_gemma":[0.9987658,0.00003152432,0.000006507859,0.000002866163,0.00003209149,0.00003970376,0.00003713609,0.000008100512,0.001076306],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4351935,"threshold_uncertainty_score":0.9942952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03537224388263877,"score_gpt":0.2278981173378121,"score_spread":0.1925258734551733,"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."}}