{"id":"W7083315449","doi":"10.1016/j.energy.2025.138665","title":"High potential of urban area originally inedible food waste for bioenergy to mitigate climate change","year":2025,"lang":"en","type":"article","venue":"Energy","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"Young Scientists Fund; Argonne National Laboratory; National Natural Science Foundation of China; United Nations Foundation; World Bank Group","keywords":"Bioenergy; Climate change; Climate change mitigation; Greenhouse gas; Renewable energy; Fossil fuel; Carbon footprint; Electricity; Resource (disambiguation)","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":[0.00017951,0.0002364359,0.0001508458,0.0009434853,0.0005695639,0.001140638,0.0002730953,0.0003999908,0.003310391],"category_scores_gemma":[0.0003163169,0.0001302735,0.0002292932,0.001335353,0.0002945002,0.0006687393,0.0005101998,0.0002009925,0.0005171882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006344909,"about_ca_system_score_gemma":0.0005853173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003341331,"about_ca_topic_score_gemma":0.01319415,"domain_scores_codex":[0.9999031,0.00002072591,0.000002609839,0.00001706529,0.00002751548,0.00002896124],"domain_scores_gemma":[0.9998246,0.00004105005,0.00001946888,0.00001726826,0.00007626651,0.00002137537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001339296,0.000302315,0.3740363,0.0008266351,0.0002592098,0.003681011,0.001079702,0.1978977,0.1665481,0.03846252,0.006809784,0.2087574],"study_design_scores_gemma":[0.00005437904,0.0004063969,0.3833817,0.000185222,0.0003718987,0.001640313,0.01174215,0.2948008,0.1850495,0.04113144,0.0811213,0.0001149035],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9637277,0.000675666,0.01130964,0.0005577832,0.000041266,0.00002147979,0.001095163,0.0002060095,0.02236529],"genre_scores_gemma":[0.9974018,0.0001394279,0.001009074,0.000009822113,0.000003761897,0.000004199358,0.0001765622,0.00001358694,0.001241665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003341331,"threshold_uncertainty_score":0.0110743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01383870903410643,"score_gpt":0.2154074157550979,"score_spread":0.2015687067209915,"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."}}