{"id":"W2585960605","doi":"10.1364/oe.25.002771","title":"Deconvolution based photoacoustic reconstruction with sparsity regularization","year":2017,"lang":"en","type":"article","venue":"Optics Express","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Deconvolution; Tikhonov regularization; Algorithm; Iterative reconstruction; Blind deconvolution; Computation; Regularization (linguistics); Computer science; Mathematics; Optics; Inverse problem; Artificial intelligence; Physics; Mathematical analysis","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008831113,0.000127921,0.0001194007,0.00004720994,0.0003251067,0.0001469413,0.0001724194,0.00006917198,0.00003083693],"category_scores_gemma":[0.00005057346,0.0001285171,0.00002456391,0.00003341943,0.0000976408,0.0003127693,0.00001549292,0.0001231037,0.000008055766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007486576,"about_ca_system_score_gemma":0.00002848767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001511834,"about_ca_topic_score_gemma":0.000006243012,"domain_scores_codex":[0.9993752,0.000008975496,0.0001162854,0.0001601751,0.0001288684,0.000210502],"domain_scores_gemma":[0.9993198,0.00002675773,0.00006818317,0.0004582565,0.00006372064,0.00006331756],"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":[0.00008854047,0.00007207006,0.00763038,0.0003491035,0.000112054,0.00003714876,0.0002536588,0.7378932,0.2383468,0.0009787153,0.0006839894,0.01355441],"study_design_scores_gemma":[0.000530857,0.00001446284,0.003086296,0.0001139154,0.00005325146,0.00002874358,0.00004005984,0.9592868,0.03628718,0.0002084739,0.0001422907,0.0002076616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2355962,0.00002632598,0.7512897,0.00002038633,0.0005147131,0.0001504631,0.00001677928,0.000215677,0.01216981],"genre_scores_gemma":[0.9745691,0.00001412775,0.02508898,0.00001350902,0.00007820781,0.00001309831,0.00001474182,0.00002692033,0.0001813452],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7389729,"threshold_uncertainty_score":0.5240776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009619820609554427,"score_gpt":0.1984041262380232,"score_spread":0.1887843056284687,"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."}}