{"id":"W4234050489","doi":"10.1017/s0890060415000517","title":"AIE volume 29 issue 4 Cover and Front matter","year":2015,"lang":"en","type":"article","venue":"Artificial intelligence for engineering design analysis and manufacturing","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of South Australia; George Mason University; Massachusetts Institute of Technology; Oregon State University; University of Toronto; Carnegie Mellon University; University College London; Drexel University; Boeing; Worcester Polytechnic Institute; Aalborg Universitet; Technische Universiteit Delft; Georgia Institute of Technology","keywords":"Front cover; Cover (algebra); Volume (thermodynamics); Front (military); Computer science; Action (physics); Content (measure theory); Environmental science; Engineering; Physics; Mathematics; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001235486,0.0009290418,0.000904283,0.003629342,0.001618804,0.008877601,0.00110577,0.002602278,0.7245609],"category_scores_gemma":[0.003684736,0.0004054507,0.000766912,0.002613751,0.0008686326,0.003548072,0.002289822,0.002490487,0.6303421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001429091,"about_ca_system_score_gemma":0.001520184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0011187,"about_ca_topic_score_gemma":0.002038749,"domain_scores_codex":[0.9986613,0.0001007202,0.00005370741,0.0001913574,0.0008670414,0.0001259099],"domain_scores_gemma":[0.9966776,0.0005637678,0.0001391695,0.0004097034,0.001498543,0.0007112161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003522768,0.00006657009,0.0001782618,0.0001878155,0.000007827713,0.00004437371,0.00002243192,0.00008644701,0.0006071854,0.003828613,0.8991315,0.09580381],"study_design_scores_gemma":[0.000003972484,0.00001010916,0.0004002007,0.00009680462,0.000002786193,0.00004907696,0.00002548888,0.0001077627,0.0001832466,0.00102015,0.9980966,0.000003698753],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0008690129,0.006572481,0.001459522,0.007369132,0.02270261,0.00009000736,0.001192845,0.0009088202,0.9588356],"genre_scores_gemma":[0.003066654,0.002694086,0.0006778893,0.001575598,0.004707448,0.00002904821,0.0008309238,0.0003447506,0.9860736],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2754391,"threshold_uncertainty_score":0.3928805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05820371184066587,"score_gpt":0.2252028823603106,"score_spread":0.1669991705196447,"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."}}