{"id":"W4413593314","doi":"10.1016/j.resconrec.2025.108547","title":"Data-driven strategies to mitigate greenhouse gas emissions intensity while sustaining global rice production","year":2025,"lang":"en","type":"article","venue":"Resources Conservation and Recycling","topic":"Crop Yield and Soil Fertility","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Greenhouse gas; Production (economics); Environmental science; Waste management; Emission intensity; Natural resource economics; Environmental engineering; Business; Engineering; Economics","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":[0.01227164,0.00100735,0.0006368998,0.001740395,0.0006268753,0.004646411,0.00302103,0.001762653,0.006195766],"category_scores_gemma":[0.02109736,0.0004138061,0.0006444821,0.002399136,0.0009778342,0.005997202,0.00278851,0.001919431,0.001594954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002390712,"about_ca_system_score_gemma":0.00908532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006648031,"about_ca_topic_score_gemma":0.0142245,"domain_scores_codex":[0.9970335,0.001233646,0.0002298772,0.0004617354,0.0007955947,0.0002456926],"domain_scores_gemma":[0.977544,0.007406087,0.002832014,0.003012779,0.008274949,0.0009301623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008755852,0.001195747,0.04705195,0.003180195,0.000775687,0.0004582629,0.000576296,0.2392487,0.03162253,0.1508837,0.07198141,0.45215],"study_design_scores_gemma":[0.0002624062,0.0005003487,0.02087753,0.001805458,0.0003908614,0.0003195986,0.003606265,0.3464832,0.0434101,0.2847882,0.2972993,0.000256722],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1470044,0.007284552,0.6315894,0.08801389,0.002368559,0.001898043,0.01598489,0.006645381,0.09921096],"genre_scores_gemma":[0.8060276,0.002818755,0.172949,0.005616888,0.0002686092,0.0005425005,0.005698305,0.0003179884,0.00576038],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01227164,"threshold_uncertainty_score":0.06489944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05075241223316568,"score_gpt":0.2837058346389864,"score_spread":0.2329534224058207,"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."}}