{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007208377,0.001147454,0.000335043,0.0004480142,0.0002486935,0.001235568,0.0007242247,0.001022475,0.001720826],"category_scores_gemma":[0.002442332,0.0004338914,0.0003429541,0.0004013508,0.0006869854,0.001250405,0.0008006701,0.001003296,0.0006039085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005302936,"about_ca_system_score_gemma":0.000802758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002588813,"about_ca_topic_score_gemma":0.002961844,"domain_scores_codex":[0.9998747,0.00002801105,0.000006556021,0.00001614462,0.00005464453,0.00001997944],"domain_scores_gemma":[0.9993574,0.0003122177,0.00007239896,0.0001146192,0.00009878782,0.00004452279],"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":[0.0002464576,0.0001476196,0.001703122,0.0001668562,0.00003411951,0.0002976971,0.0003864232,0.7909607,0.1636817,0.01258693,0.001036424,0.02875189],"study_design_scores_gemma":[0.00001193188,0.0000215964,0.0001668846,0.000006842211,0.000005283904,0.00004194853,0.00002899127,0.9719799,0.02570461,0.001455434,0.000563539,0.00001312014],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2379558,0.00009213182,0.7564564,0.0002124873,0.00004352019,0.00003614836,0.000167318,0.001761633,0.003274589],"genre_scores_gemma":[0.5655888,0.0001520579,0.4310141,0.00009539638,0.00001027761,0.00004969132,0.0002890766,0.0006620659,0.002138504],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002588813,"threshold_uncertainty_score":0.005756676,"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."}}