{"id":"W136966946","doi":"10.1109/tci.2015.2498402","title":"Undersampled Phase Retrieval With Outliers","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Computational Imaging","topic":"Advanced X-ray Imaging Techniques","field":"Physics and Astronomy","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Israel Science Foundation","keywords":"Computer science; Outlier; Phase retrieval; Computer vision; Artificial intelligence; Phase (matter); Remote sensing; Mathematics; Geology; Physics; Fourier transform","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001047244,0.0006814188,0.00102755,0.0006883368,0.0003018176,0.001064586,0.001190382,0.001071972,0.0008670816],"category_scores_gemma":[0.004337919,0.0004639799,0.0007195306,0.0008588625,0.00103124,0.002091267,0.001408768,0.001240466,0.0004306944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005310648,"about_ca_system_score_gemma":0.0009287777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001320344,"about_ca_topic_score_gemma":0.001037211,"domain_scores_codex":[0.9990282,0.0002006382,0.00004728192,0.0001949132,0.0004733175,0.00005566062],"domain_scores_gemma":[0.998962,0.0003623917,0.0001838191,0.0002459032,0.0002149876,0.00003084671],"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":[0.0002385938,0.00005399618,0.001415191,0.0001724736,0.00008931514,0.000321465,0.0002499381,0.7417887,0.06019856,0.06052445,0.001540243,0.133407],"study_design_scores_gemma":[0.00001654533,0.0000525351,0.000287706,0.0000121742,0.00001236256,0.0001826473,0.00002631513,0.9619665,0.01766415,0.01687559,0.002872047,0.00003135276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007563516,0.000070286,0.9918423,0.00006443333,0.00001722383,0.00000915793,0.00002472259,0.0001472376,0.0002611937],"genre_scores_gemma":[0.2778775,0.0003995802,0.7188999,0.0001709856,0.0001069412,0.00007713066,0.0003032369,0.0001642629,0.002000549],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001320344,"threshold_uncertainty_score":0.005538404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02960783974726054,"score_gpt":0.3191181555736223,"score_spread":0.2895103158263618,"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."}}