{"id":"W3034241391","doi":"10.5539/jfr.v9n4p10","title":"Developing a Software Tool to Estimate Food Transportation Carbon Emissions","year":2020,"lang":"en","type":"article","venue":"Journal of Food Research","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sustainability; Sustainable transport; Transport engineering; Production (economics); Business; Environmental science; Environmental economics; Engineering; Economics; Ecology","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":[0.000384924,0.00008399694,0.0001552918,0.0001637392,0.00009951894,0.00003777718,0.0002098166,0.0000601238,0.00002612542],"category_scores_gemma":[0.0002059646,0.00006981981,0.00005268134,0.0005739372,0.0000111105,0.0001208781,0.00001470405,0.0005577753,0.000006808628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007537934,"about_ca_system_score_gemma":0.0001731862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001286683,"about_ca_topic_score_gemma":0.000006493289,"domain_scores_codex":[0.9987838,0.00002562527,0.0003298857,0.0000831519,0.0004982498,0.0002792742],"domain_scores_gemma":[0.9992656,0.00006427425,0.00003110656,0.00008153226,0.0002578156,0.0002997156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006081894,0.0001262613,0.01159711,0.002206267,0.0005574428,0.0003174519,0.02015374,0.3715297,0.3128441,0.000867029,0.01640871,0.262784],"study_design_scores_gemma":[0.003918084,0.01074995,0.0591751,0.003680669,0.00008227406,0.0002021668,0.001410186,0.1223976,0.6466795,0.00200651,0.1481255,0.001572371],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884492,0.000345389,0.00896415,0.001824601,0.00009753106,0.0001042352,0.000007966535,0.00004266455,0.0001643022],"genre_scores_gemma":[0.9863034,0.00006604699,0.01335774,0.00003985906,0.0001906363,0.000004628363,0.00000132525,0.00002247873,0.00001387492],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3338354,"threshold_uncertainty_score":0.2847169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08917537226567646,"score_gpt":0.3606953246802319,"score_spread":0.2715199524145554,"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."}}