{"id":"W4289779044","doi":"10.1016/j.spc.2022.07.030","title":"Spatially resolved inventory and emissions modelling for pea and lentil life cycle assessment","year":2022,"lang":"en","type":"article","venue":"Sustainable Production and Consumption","topic":"Agriculture Sustainability and Environmental Impact","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Alberta Agriculture and Forestry","keywords":"Environmental science; Greenhouse gas; Production (economics); Life-cycle assessment; Climate change; Fertilizer; Agriculture; Food security; Tillage; Environmental resource management; Geography; Agronomy; Economics; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005648672,0.0001258622,0.0001127571,0.00003911996,0.001207045,0.00005548399,0.00004596501,0.00003857448,0.0003034448],"category_scores_gemma":[0.00006813111,0.0001183502,0.00002432854,0.00008297077,0.0002060299,0.0003732488,0.0003044247,0.0001513601,0.000001166728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003683015,"about_ca_system_score_gemma":0.00002431723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002747532,"about_ca_topic_score_gemma":0.00001667322,"domain_scores_codex":[0.9988485,0.00009402826,0.0001630777,0.0004373313,0.0001884167,0.0002686628],"domain_scores_gemma":[0.9996099,0.00001895524,0.00007393317,0.0001253046,0.00001280763,0.0001590673],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001127599,0.001375394,0.3188336,0.001752493,0.0001317143,0.00002346251,0.01321753,0.5700611,0.007696224,0.006794048,0.009843091,0.06914369],"study_design_scores_gemma":[0.003459312,0.001382274,0.3120574,0.00005254585,0.000363147,0.0002010737,0.1153365,0.3293827,0.0004791105,0.03565848,0.1998812,0.001746248],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992347,0.000636922,0.003987907,0.001870062,0.00007578664,0.0008226875,0.000005834627,0.00003936478,0.0002144086],"genre_scores_gemma":[0.9948386,0.0004113712,0.0007138641,0.0001159822,0.00004171884,0.0001330352,0.00002058941,0.00001046148,0.003714392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2406785,"threshold_uncertainty_score":0.9283738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0161288633450626,"score_gpt":0.2456084001267995,"score_spread":0.2294795367817369,"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."}}