{"id":"W4385588001","doi":"10.1007/978-3-030-97940-9_17","title":"An Integrated AI-Multiple Criteria Decision-Making Framework to Improve Sustainable Energy Planning in Manufacturing Systems: A Case Study","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Energy Efficiency and Management","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Multiple-criteria decision analysis; Task (project management); Management science; Energy planning; Energy (signal processing); Sustainable development; Computer science; Engineering; Process management; Risk analysis (engineering); Operations research; Systems engineering; Business; Renewable energy","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008551265,0.0009165363,0.000986245,0.001691269,0.0003430389,0.00056567,0.0007155941,0.0006551177,0.0002924078],"category_scores_gemma":[0.0003031295,0.0008197247,0.0001518518,0.0003130943,0.00003291524,0.0003146046,0.0007238336,0.0007760324,0.00006080515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006716655,"about_ca_system_score_gemma":0.00009528801,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04097664,"about_ca_topic_score_gemma":0.01882874,"domain_scores_codex":[0.9955712,0.0001157055,0.00116442,0.001500674,0.0005999607,0.001048048],"domain_scores_gemma":[0.9970139,0.000937663,0.0002436408,0.001354858,0.0001964083,0.000253476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003079839,0.0002916618,0.00005696507,0.000246045,0.0002808904,0.08747935,0.003160245,0.5922359,0.0000115102,0.2909242,0.0007637623,0.02424147],"study_design_scores_gemma":[0.004084928,0.004617227,0.0001687648,0.01450969,0.0005480228,0.0008996342,0.2938639,0.1315373,0.0002198604,0.08933017,0.4514372,0.008783349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1288783,0.0006002457,0.3488271,0.00008933072,0.007857409,0.005015613,0.00007832913,0.003716718,0.504937],"genre_scores_gemma":[0.8093518,0.000007954873,0.00122067,0.0003128335,0.0002657216,0.0003046514,0.00003370392,0.00025057,0.1882521],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6804736,"threshold_uncertainty_score":0.9994254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01761389962839042,"score_gpt":0.3017376305294016,"score_spread":0.2841237309010111,"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."}}