{"id":"W25958209","doi":"10.1007/978-3-642-29069-5_55","title":"Using a New Economic Model with LCA-Based Carbon Emission Inputs for Process Parameter Selection in Machining","year":2012,"lang":"en","type":"book-chapter","venue":"","topic":"Energy Efficiency and Management","field":"Energy","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Machining; Selection (genetic algorithm); Sprocket; Process (computing); Computer science; Work (physics); Process engineering; Model selection; Industrial engineering; Manufacturing engineering; Engineering; Mechanical engineering; Artificial intelligence","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":[0.0007653298,0.000969413,0.00100384,0.00050477,0.0006760265,0.001802671,0.001545442,0.001973469,0.004178607],"category_scores_gemma":[0.001456499,0.0007053615,0.001414373,0.001039136,0.0006879865,0.002146045,0.000721538,0.001687224,0.0005244891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001771122,"about_ca_system_score_gemma":0.001304876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01558919,"about_ca_topic_score_gemma":0.01750925,"domain_scores_codex":[0.9997507,0.0000853233,0.00001368523,0.00005180867,0.00007769961,0.00002079757],"domain_scores_gemma":[0.9995401,0.0003080339,0.0000337257,0.00002582638,0.00007760512,0.0000148294],"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":[0.00001201097,0.0000216513,0.0001368908,0.00002435634,0.00002108808,0.00002927522,0.000006878608,0.9872637,0.0004183876,0.007821324,0.0003232763,0.003921072],"study_design_scores_gemma":[0.000005368249,0.000005974146,0.00006196866,0.000002997396,0.000009132353,0.000006864171,0.000002044752,0.9953656,0.0001669526,0.003720665,0.0006470123,0.000005308501],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03964679,0.0007031642,0.9202782,0.001070436,0.0003285597,0.000118063,0.0007146006,0.0004369022,0.03670327],"genre_scores_gemma":[0.7403543,0.001361218,0.2177858,0.0003580889,0.0001953625,0.0005838523,0.0007431394,0.0003165649,0.03830164],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01558919,"threshold_uncertainty_score":0.03099686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0459753558880172,"score_gpt":0.2743378617373086,"score_spread":0.2283625058492914,"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."}}