{"id":"W2032765157","doi":"10.1002/cmr.a.21256","title":"A pixel is an artifact: On the necessity of zero‐filling in fourier imaging","year":2013,"lang":"en","type":"article","venue":"Concepts in Magnetic Resonance Part A","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Medical Council of Canada","funders":"","keywords":"Pixel; Computer vision; Artificial intelligence; Fourier transform; Computer science; Artifact (error); Interpolation (computer graphics); Convolution (computer science); Frequency domain; Discrete Fourier transform (general); Image (mathematics); Algorithm; Mathematics; Fourier analysis; Mathematical analysis","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":[0.0002053405,0.000122691,0.0002254193,0.00005850593,0.00004368652,0.0000125703,0.0001600746,0.00004674015,0.0006660262],"category_scores_gemma":[0.0000903293,0.00008986989,0.00003937024,0.0002985021,0.0001865724,0.00009540995,0.00003962252,0.0002419592,0.00003266495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000392946,"about_ca_system_score_gemma":0.00003466603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001073931,"about_ca_topic_score_gemma":0.00002022442,"domain_scores_codex":[0.9989329,0.00004170429,0.0003312248,0.0002739646,0.0001726331,0.0002475707],"domain_scores_gemma":[0.999142,0.0001214544,0.00008567048,0.0005281317,0.00006295697,0.0000597665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00007325154,0.0004263601,0.07979614,0.00003681564,0.000001600425,0.00001234253,0.002631747,0.00008875412,0.01113416,0.008132022,0.005257122,0.8924097],"study_design_scores_gemma":[0.002898402,0.0007959505,0.5614889,0.001927421,0.00003157642,0.00002062651,0.002199121,0.06508178,0.03061574,0.06075977,0.2735035,0.0006772444],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9833788,0.002150629,0.004095627,0.004654521,0.00003561559,0.001128861,0.000006480176,0.00004142924,0.004508047],"genre_scores_gemma":[0.9863461,0.0002428332,0.01072777,0.001626443,0.00003872821,0.00040023,0.000003042961,0.00001585595,0.0005989582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8917325,"threshold_uncertainty_score":0.729252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03029111544611267,"score_gpt":0.3284357909494461,"score_spread":0.2981446755033334,"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."}}