{"id":"W4404293931","doi":"10.1109/tgrs.2024.3496812","title":"Integrated Networks for Viscoelastic FWI: Mapping From Q to Relaxation Variables and Quantifying Modeling Error","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Geoscience and Remote Sensing","topic":"Tribology and Wear Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Viscoelasticity; Computer science; Remote sensing; Algorithm; Geology; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002657101,0.001356517,0.0005930377,0.0006702598,0.0004354384,0.001208437,0.001724158,0.001194617,0.00179823],"category_scores_gemma":[0.009678672,0.0006211762,0.0005683101,0.0007049167,0.001026144,0.002724872,0.001664643,0.002547845,0.0003469696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00129821,"about_ca_system_score_gemma":0.001324005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008474627,"about_ca_topic_score_gemma":0.0073682,"domain_scores_codex":[0.9994216,0.0001593365,0.00003041077,0.0001326647,0.0002113166,0.00004471578],"domain_scores_gemma":[0.9979121,0.001266104,0.0002637566,0.0001959153,0.000307798,0.00005435703],"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":[0.00004370667,0.00002919817,0.001003914,0.00006232008,0.00003292285,0.0000569769,0.00006269917,0.9544277,0.002455562,0.01454482,0.0004802622,0.0267999],"study_design_scores_gemma":[0.00000111455,0.000006318989,0.00005297627,0.000005965084,0.000002480038,0.000004147063,0.000002836268,0.9963269,0.000399468,0.003022212,0.0001724374,0.000003218234],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01338159,0.0002553697,0.9842387,0.0002846376,0.000035967,0.00002600472,0.0000732045,0.0003490084,0.001355435],"genre_scores_gemma":[0.62226,0.0005681386,0.3729987,0.0002769355,0.00007552278,0.0002328849,0.0004325651,0.0002912806,0.002864005],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008474627,"threshold_uncertainty_score":0.01685059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03091669446190909,"score_gpt":0.2536921683101552,"score_spread":0.2227754738482461,"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."}}