{"id":"W4412720425","doi":"10.1016/j.bspc.2025.108355","title":"CCSMRI: Circular compressed sensing MRI","year":2025,"lang":"en","type":"article","venue":"Biomedical Signal Processing and Control","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Compressed sensing; Computer science; Artificial intelligence; Computer vision; Pattern recognition (psychology)","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":[0.0005870935,0.0009124763,0.0004186061,0.001345179,0.0002858058,0.001314488,0.0006271298,0.001057048,0.03029783],"category_scores_gemma":[0.002947515,0.0002272716,0.0001805852,0.001412285,0.000641295,0.0008446359,0.0009326809,0.001050801,0.01516384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002814963,"about_ca_system_score_gemma":0.0006983884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009163809,"about_ca_topic_score_gemma":0.001148897,"domain_scores_codex":[0.9995622,0.00007766,0.00002906118,0.00009851056,0.0002041165,0.00002845732],"domain_scores_gemma":[0.9988561,0.0003839174,0.000151369,0.0001278592,0.0003619633,0.0001187891],"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":[0.0003540209,0.00008486938,0.0004405883,0.0008023333,0.00003608073,0.0004508363,0.00007679069,0.007464198,0.06051687,0.08494131,0.2347231,0.610109],"study_design_scores_gemma":[0.0001121834,0.0002987087,0.002414916,0.0004102165,0.00006165729,0.003899515,0.0001024818,0.2163721,0.0840109,0.07125092,0.6208781,0.0001882132],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004435512,0.005893648,0.922896,0.003218073,0.002416346,0.0003286147,0.005035636,0.01361725,0.04215892],"genre_scores_gemma":[0.1029131,0.009636302,0.7969289,0.004449375,0.004925425,0.001016869,0.008529478,0.005476075,0.06612451],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03029783,"threshold_uncertainty_score":0.1013564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009002053568642409,"score_gpt":0.2900105044109555,"score_spread":0.2810084508423131,"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."}}