{"id":"W2098083372","doi":"10.1115/detc2008-49924","title":"Multi-Users Dynamic Maintenance Document for Complex Mechanical Products: Application for Automobile","year":2008,"lang":"en","type":"article","venue":"","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Reuse; Personalization; Computer science; Product (mathematics); Product lifecycle; Point (geometry); Field (mathematics); Automotive industry; Systems engineering; Human–computer interaction; Software engineering; Process management; New product development; World Wide Web; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001381442,0.0004378709,0.000567538,0.0007229439,0.000466104,0.0010729,0.001092327,0.0009336829,0.001923934],"category_scores_gemma":[0.002502618,0.0002868516,0.000345529,0.0008017569,0.0002988626,0.001262222,0.00104274,0.0005989604,0.0006651053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003734395,"about_ca_system_score_gemma":0.0004705056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002015425,"about_ca_topic_score_gemma":0.002043343,"domain_scores_codex":[0.999253,0.0002379778,0.00006593864,0.0001471921,0.0002497659,0.00004605151],"domain_scores_gemma":[0.9977629,0.0008241094,0.0001663288,0.00073099,0.0003710958,0.000144588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001073229,0.0008587855,0.01221986,0.001045354,0.0001406946,0.002305456,0.003116047,0.02498785,0.1016564,0.01037206,0.01163408,0.8305901],"study_design_scores_gemma":[0.0004304203,0.001403741,0.04054763,0.0005431001,0.0004163605,0.00644635,0.00279857,0.5371173,0.1574969,0.01213426,0.240239,0.0004263216],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2505848,0.001006445,0.7194453,0.000622893,0.00005676573,0.0005142665,0.0007905004,0.02185523,0.005123889],"genre_scores_gemma":[0.5299948,0.0004443088,0.4630052,0.0001095046,0.00004124116,0.0001883257,0.0009920334,0.0004950375,0.004729491],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002015425,"threshold_uncertainty_score":0.007305861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01707139230255206,"score_gpt":0.2452630660224617,"score_spread":0.2281916737199096,"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."}}