{"id":"W3196002354","doi":"10.1109/antem51107.2021.9518947","title":"Using Lossy Green’s Functions to Improve Back-Propagated Reconstructions of Material Interfaces inside Resonant Enclosures","year":2021,"lang":"en","type":"article","venue":"","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Lossy compression; Green S; Computer science; Physics; Acoustics; Materials science; Electronic engineering; Electrical engineering; Mathematics; Engineering; Mathematical analysis; Artificial intelligence","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":[0.00005207997,0.0001154581,0.0001856621,0.00005962055,0.00006435739,0.00002997144,0.00007548556,0.00005475962,0.0007466303],"category_scores_gemma":[0.00003102491,0.0001066622,0.00005486152,0.0003529112,0.00004101759,0.00007437333,0.0000626301,0.00008786986,0.00009426421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003151759,"about_ca_system_score_gemma":0.00003154017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003227242,"about_ca_topic_score_gemma":0.0001305922,"domain_scores_codex":[0.9992521,0.00003148415,0.0002837512,0.0001909651,0.00007639663,0.0001652459],"domain_scores_gemma":[0.99946,0.00004147225,0.0000284016,0.0002634757,0.0001245899,0.00008204093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000005091082,0.00002451224,0.0000550326,0.00003633241,0.00003333037,8.328324e-7,0.00004592507,0.0008443068,0.9799235,0.0006063682,0.0002416487,0.01818314],"study_design_scores_gemma":[0.000149891,0.00004216934,0.001878494,0.00004791824,0.00003890047,0.00002148414,0.0003921858,0.005639213,0.985343,0.001413082,0.004819727,0.0002138695],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9553938,0.00002726514,0.04038342,0.0001640214,0.000665119,0.0001598288,0.0001642252,0.0001170284,0.002925308],"genre_scores_gemma":[0.8656392,0.000007102354,0.1332511,0.00002448997,0.0001496794,0.00003233248,0.00001335348,0.00002406729,0.0008587015],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09286771,"threshold_uncertainty_score":0.8175078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02929671394260572,"score_gpt":0.2687679887148777,"score_spread":0.239471274772272,"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."}}