{"id":"W2043778571","doi":"10.1109/usnc-ursi.2013.6715514","title":"A source wavelet deconvolution approach to improve the spatial resolution for radar-based breast imaging system","year":2013,"lang":"en","type":"article","venue":"","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Deconvolution; Wavelet; Computer science; Image resolution; Microwave imaging; Radar imaging; Iterative reconstruction; Computer vision; Radar; Breast imaging; Artificial intelligence; Algorithm; Mammography; Microwave; Telecommunications","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":[0.0002976821,0.0001798417,0.0001770794,0.0001155402,0.0001761822,0.0001643714,0.0001872856,0.00003884946,0.00001556994],"category_scores_gemma":[0.00001373616,0.0001348287,0.0001303434,0.0001589504,0.0000260163,0.00009217459,0.00002490112,0.0001018228,0.00008177628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001987477,"about_ca_system_score_gemma":0.0000150844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001955618,"about_ca_topic_score_gemma":0.00002105416,"domain_scores_codex":[0.998952,0.00003469919,0.0002540793,0.0002602162,0.0001278475,0.0003712016],"domain_scores_gemma":[0.9993765,0.00004832626,0.00003457149,0.0003666347,0.00008157353,0.00009236919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006197595,0.0001170464,0.0009924253,0.001330232,0.0003577262,8.128005e-7,0.001093799,0.3207206,0.3251303,0.0004991959,0.09543661,0.2542592],"study_design_scores_gemma":[0.0002784695,0.000007375791,0.0006080217,0.00002723587,0.00004437314,0.00002059734,0.0003306581,0.9938895,0.003124063,0.000006983874,0.001470849,0.0001919113],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02204192,0.00005257236,0.9742867,0.0007120846,0.0001702259,0.0005374171,0.00001829801,0.0005274347,0.001653346],"genre_scores_gemma":[0.9815537,3.367156e-7,0.01742879,0.0001638146,0.000203979,0.0002639498,0.00003247007,0.00004277383,0.0003101633],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9595118,"threshold_uncertainty_score":0.5498157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004632479560098371,"score_gpt":0.1735410136854468,"score_spread":0.1689085341253484,"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."}}