{"id":"W3146972933","doi":"10.1109/isam.2009.5376926","title":"Airframe dismantling optimization for aerospace aluminum valorization","year":2009,"lang":"en","type":"article","venue":"","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Airframe; Aerospace; Airplane; Process (computing); Upgrade; Profitability index; Automotive industry; Computer science; Manufacturing engineering; Engineering; Systems engineering; Aerospace engineering","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":[0.00005217911,0.0001074067,0.00009098482,0.00005448895,0.0000694983,0.00006297824,0.0000621757,0.00007023171,0.00006934904],"category_scores_gemma":[0.0000189789,0.0001061623,0.00003149697,0.0001027517,0.00000459033,0.0002295945,0.000003806526,0.00004159086,0.000004495017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002843025,"about_ca_system_score_gemma":0.00000477724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001009215,"about_ca_topic_score_gemma":9.123385e-7,"domain_scores_codex":[0.9994948,0.000002926202,0.0001392751,0.0001259152,0.00007751731,0.0001595769],"domain_scores_gemma":[0.9997763,0.00001536498,0.00002247787,0.00009881461,0.00004787269,0.00003914518],"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":[0.000003715236,0.000007838891,0.00001330383,0.00003076408,0.000003911769,8.624129e-8,0.00007332286,0.9929987,0.0001594546,0.001117591,0.000344229,0.00524713],"study_design_scores_gemma":[0.000218867,0.00002493255,0.0001555748,0.00001125517,0.000008354024,5.045083e-7,0.00001634229,0.9913882,0.006847399,0.0003782952,0.0008021298,0.0001481311],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00340453,0.00004572071,0.9924023,0.000167815,0.000221766,0.000225629,0.000002178795,0.0006098868,0.002920142],"genre_scores_gemma":[0.8538346,0.00008378184,0.1453642,0.00009066734,0.0001302845,0.0000191955,0.00009812281,0.00002627654,0.0003529119],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8504301,"threshold_uncertainty_score":0.4329171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007631016557794949,"score_gpt":0.2069103343420139,"score_spread":0.199279317784219,"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."}}