{"id":"W4411391268","doi":"10.3389/fendo.2025.1581328","title":"Assessment of reconstruction accuracy for under-sampled 31P-MRS data using compressed sensing and a low rank Hankel matrix completion approach","year":2025,"lang":"en","type":"article","venue":"Frontiers in Endocrinology","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Matrix completion; Rank (graph theory); Compressed sensing; Hankel matrix; Matrix (chemical analysis); Algorithm; Low-rank approximation; Computer science; Mathematics; Statistics; Pattern recognition (psychology); Artificial intelligence; Combinatorics; Mathematical analysis; Chemistry; Computational chemistry","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":[0.004716381,0.0008089272,0.0006761428,0.001117273,0.000332421,0.0007839148,0.0005359941,0.001326734,0.001006041],"category_scores_gemma":[0.01947358,0.0002715844,0.0004987983,0.0008253334,0.0006718411,0.0009127576,0.0006896533,0.000685479,0.0002889489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003334199,"about_ca_system_score_gemma":0.0006592398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002351093,"about_ca_topic_score_gemma":0.001893061,"domain_scores_codex":[0.9982644,0.0005832791,0.000166314,0.0002308028,0.0006314865,0.0001237032],"domain_scores_gemma":[0.9895927,0.006902773,0.0007874587,0.0008020612,0.001710971,0.0002040638],"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":[0.006276333,0.0005793645,0.01607996,0.001230358,0.0004419934,0.0008135482,0.0007952873,0.4440843,0.2922201,0.00407631,0.0012114,0.2321911],"study_design_scores_gemma":[0.00003644122,0.0006309916,0.006923775,0.00003672784,0.00006535417,0.0003816817,0.0000968633,0.9272187,0.06284538,0.001030477,0.0006642458,0.00006924839],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6064267,0.00131547,0.3895867,0.0003087328,0.00008130501,0.0001061115,0.0004579668,0.0007087104,0.001008384],"genre_scores_gemma":[0.740935,0.0006425118,0.2564145,0.00006218565,0.00002736081,0.00007352178,0.001050362,0.0001810098,0.0006135639],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.004716381,"threshold_uncertainty_score":0.02494293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06482304548695318,"score_gpt":0.4006145204257357,"score_spread":0.3357914749387825,"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."}}