{"id":"W7117121015","doi":"10.1016/j.array.2025.100652","title":"Green AI techniques for reducing energy consumption in AI systems","year":2025,"lang":"en","type":"article","venue":"Array","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"","keywords":"Neuromorphic engineering; Inference; Transparency (behavior); Software deployment; Energy consumption; Key (lock); Efficient energy use; Artificial neural network","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001039426,0.00007092115,0.00009907273,0.0001101085,0.0000759457,0.00004395279,0.0003421532,0.00004347465,7.217818e-7],"category_scores_gemma":[0.00001144715,0.00007160715,0.00002378219,0.0003289909,0.00002107471,0.0002406133,0.00005214939,0.00006856426,0.000003325087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005840056,"about_ca_system_score_gemma":0.00002469566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001219002,"about_ca_topic_score_gemma":0.00003981262,"domain_scores_codex":[0.9993118,0.00002662524,0.0001752188,0.0002712749,0.00005693837,0.0001581362],"domain_scores_gemma":[0.9994188,0.0001070376,0.00004576389,0.0003641501,0.00004169705,0.00002257879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006724082,0.00003987546,0.0007199374,0.0000597736,0.000008499549,0.000001281193,0.0001174672,0.001945183,0.03595981,0.8170916,0.006873981,0.1371759],"study_design_scores_gemma":[0.0006388833,0.0000992213,0.00145889,0.0005869715,0.00001344656,0.00001659665,0.00002169223,0.2523556,0.1936868,0.1585138,0.3920271,0.0005809764],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004326426,0.000205835,0.9944565,0.003491754,0.0001620317,0.0002781544,0.00000144714,0.0002184073,0.0007531691],"genre_scores_gemma":[0.9422841,0.00004981452,0.0537976,0.00188493,0.00008204632,0.0007677433,0.000005558434,0.000008012084,0.001120164],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9418515,"threshold_uncertainty_score":0.2920055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01874840495903099,"score_gpt":0.3021264838453107,"score_spread":0.2833780788862797,"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."}}