{"id":"W2804106515","doi":"10.1002/mp.13000","title":"Technical Note: Harmonic analysis applied to <scp>MR</scp> image distortion fields specific to arbitrarily shaped volumes","year":2018,"lang":"en","type":"article","venue":"Medical Physics","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"Princess Margaret Cancer Foundation","keywords":"Cuboid; Imaging phantom; Mathematical analysis; Cylinder; Laplace's equation; Finite element method; Boundary value problem; Harmonic; Method of mean weighted residuals; Linearization; Mathematics; Spherical harmonics; Scanner; Distortion (music); Quadratic equation; Ellipsoid; Physics; Geometry; Optics; Acoustics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006598503,0.0002738449,0.000468429,0.0002291194,0.0001734115,0.0002104764,0.001705378,0.0002305336,0.0002525944],"category_scores_gemma":[0.0006794882,0.0002546765,0.000201942,0.002653446,0.0003089534,0.0003108633,0.0006471489,0.0005176482,0.0009000718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001683905,"about_ca_system_score_gemma":0.0001501186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003181777,"about_ca_topic_score_gemma":0.0000272311,"domain_scores_codex":[0.9961624,0.0000739218,0.0005769213,0.0008802751,0.00172773,0.0005787674],"domain_scores_gemma":[0.9973738,0.0002983316,0.00012629,0.001030981,0.0001951231,0.000975541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001557966,0.0005385505,0.0001148596,0.00003067835,0.00009353484,0.00005288647,0.002032203,0.000006948482,0.04392268,0.002971702,0.2163543,0.7338661],"study_design_scores_gemma":[0.001339315,0.001386763,0.008508126,0.00013979,0.0003459477,0.0000152713,0.00009562749,0.03292889,0.9033504,0.02399793,0.02692498,0.0009669694],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002667801,0.00001496339,0.9906704,0.001883646,0.0003064557,0.0004505306,0.000005769086,0.0006920581,0.003308335],"genre_scores_gemma":[0.6863852,0.00001234768,0.3019199,0.01006008,0.001059918,0.0001617227,0.00003234276,0.00002825335,0.0003402899],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8594277,"threshold_uncertainty_score":0.9999905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01630163193930066,"score_gpt":0.2880069241796368,"score_spread":0.2717052922403361,"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."}}