{"id":"W1497010967","doi":"10.1109/icecs.1996.582667","title":"Selective reconstruction of objects from the Radon transform using the generalized instantaneous matched-filter approach","year":2002,"lang":"en","type":"article","venue":"","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Orthogonalization; Radon transform; Object (grammar); Context (archaeology); Filter (signal processing); Radon; Computer vision; Iterative reconstruction; Set (abstract data type); Artificial intelligence; Computer science; Algorithm; Projection (relational algebra); Mathematics; Physics","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":[0.0003645178,0.0003865258,0.0005994227,0.0005417678,0.0001041244,0.0005284232,0.0004627092,0.0005711703,0.0005661363],"category_scores_gemma":[0.000528936,0.0002196949,0.0005288172,0.0004294123,0.0004573247,0.0008108751,0.0005365673,0.0004386253,0.0002653403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001817524,"about_ca_system_score_gemma":0.0002352856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002887845,"about_ca_topic_score_gemma":0.0003886557,"domain_scores_codex":[0.9998437,0.00003921976,0.000008967477,0.00002545613,0.00006943358,0.00001310714],"domain_scores_gemma":[0.9999012,0.00004603171,0.00001365298,0.00001894294,0.0000142939,0.000005852359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002230812,0.00002953042,0.000700786,0.0009132161,0.0001862614,0.001326109,0.0001883151,0.1138801,0.2935994,0.1448305,0.00209377,0.4420289],"study_design_scores_gemma":[0.00003530874,0.0002223135,0.001651673,0.00007629867,0.0001955889,0.003882465,0.00009456952,0.7830929,0.1205566,0.06286575,0.02723245,0.00009419974],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008712196,0.001305397,0.9885737,0.00006604218,0.00002664333,0.000009789977,0.00001745978,0.0001401425,0.001148695],"genre_scores_gemma":[0.210533,0.007371995,0.7779021,0.00009340112,0.0001657646,0.00005391402,0.0001721836,0.00007678982,0.003630833],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0005994227,"threshold_uncertainty_score":0.001927733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04661158083910654,"score_gpt":0.2806095021123423,"score_spread":0.2339979212732358,"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."}}