{"id":"W2900119318","doi":"","title":"Robust domain decomposition methods in industrial context applied to large business cases","year":2017,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Computer science; Context (archaeology); Decomposition; Domain (mathematical analysis); Mathematics; Geology","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":[0.003655273,0.0003434047,0.0004906873,0.000207335,0.0004269576,0.0004768158,0.0008663306,0.0002667362,0.0003665521],"category_scores_gemma":[0.0001971467,0.0003727925,0.0001595012,0.0002737025,0.00009542939,0.0001090723,0.00105711,0.0008395381,0.00002882877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009449021,"about_ca_system_score_gemma":0.0002163214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002229247,"about_ca_topic_score_gemma":0.0009748373,"domain_scores_codex":[0.9951686,0.002949442,0.0005180576,0.0007460414,0.000225587,0.0003922336],"domain_scores_gemma":[0.9963251,0.0006921468,0.000501735,0.001531324,0.0007476841,0.0002019491],"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":[0.000224105,0.002157218,0.007120893,0.0001189011,0.0002220746,0.00001484191,0.007837073,0.009127719,0.004950938,0.3214641,0.009871553,0.6368906],"study_design_scores_gemma":[0.02207167,0.000005562735,0.03712048,0.01893414,0.0005762714,0.00005921109,0.004713566,0.1235658,0.2128777,0.1201236,0.4508175,0.009134493],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1689309,0.0001235212,0.7859637,0.004699565,0.0005447007,0.0009010312,0.0001323298,0.00008857252,0.03861565],"genre_scores_gemma":[0.9441178,0.0000277948,0.05229829,0.00008283929,0.0001930322,0.0002114395,0.0008038658,0.00004308028,0.002221884],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7751868,"threshold_uncertainty_score":0.9998724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05611385064577927,"score_gpt":0.3145296019252195,"score_spread":0.2584157512794402,"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."}}