{"id":"W4409576455","doi":"10.61091/jcmcc127a-102","title":"Research on the Evaluation of the Efficacy of Comprehensive Agricultural Energy Electricity Substitution in the Environment of Energy Saving and Emission Reduction Based on Fuzzy Clustering Algorithm","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Power Systems and Renewable Energy","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Substitution (logic); Reduction (mathematics); Electricity; Cluster analysis; Fuzzy logic; Energy (signal processing); Agriculture; Algorithm; Environmental economics; Computer science; Environmental science; Engineering; Mathematics; Artificial intelligence; Economics; Electrical engineering; Statistics; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002653053,0.0007116911,0.0009191578,0.002133738,0.0006668846,0.001787517,0.0008673816,0.0009644025,0.001310333],"category_scores_gemma":[0.005102091,0.0002555411,0.0009307554,0.001893288,0.000436277,0.00224085,0.0005116882,0.0004344275,0.0001984796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001352719,"about_ca_system_score_gemma":0.001487803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01017753,"about_ca_topic_score_gemma":0.004951436,"domain_scores_codex":[0.9983815,0.0004521678,0.0001207544,0.0002829237,0.0006281481,0.0001344302],"domain_scores_gemma":[0.9980699,0.0008233982,0.0001419048,0.0001023813,0.0007946094,0.00006767797],"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":[0.0004335626,0.000359141,0.02347017,0.0004232225,0.0004565925,0.0001059972,0.0003588208,0.57911,0.007516187,0.01732612,0.002107122,0.368333],"study_design_scores_gemma":[0.00001847474,0.0001223568,0.004525391,0.00002541013,0.00006343715,0.00004082134,0.0001738621,0.9892961,0.002655158,0.002432565,0.0006239426,0.00002245162],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3653589,0.002067457,0.6156798,0.0006660644,0.00009862046,0.0002239555,0.0001287618,0.000463602,0.01531292],"genre_scores_gemma":[0.9059303,0.0009284485,0.09075353,0.00007311218,0.00003110003,0.00009190843,0.0001429012,0.00002892336,0.002019879],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01017753,"threshold_uncertainty_score":0.02023655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03025229144641468,"score_gpt":0.2890373451191855,"score_spread":0.2587850536727708,"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."}}