{"id":"W4411968993","doi":"10.1016/j.jneumeth.2025.110523","title":"Comparison of MRS acquisition methods for separation of overlapping signals at 3 T","year":2025,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Health Science Centre; Alberta Children's Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Children's Hospital Research Institute; Arthritis Society; Hotchkiss Brain Institute; University of Calgary","keywords":"Separation (statistics); Computer science; Artificial intelligence; Psychology; Pattern recognition (psychology); Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004139647,0.0006760822,0.0005624656,0.001154869,0.0003033651,0.0008497289,0.0005501523,0.0008097818,0.001291201],"category_scores_gemma":[0.01148886,0.0003775765,0.000497793,0.0006190811,0.0003661898,0.0009033736,0.0004679323,0.0006124452,0.0005793414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000353237,"about_ca_system_score_gemma":0.0004732294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006552135,"about_ca_topic_score_gemma":0.001182441,"domain_scores_codex":[0.9989411,0.0003768407,0.0001205288,0.0001736701,0.0003286543,0.00005921781],"domain_scores_gemma":[0.9929147,0.003678306,0.0007128675,0.0003610558,0.002124265,0.0002088032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01387291,0.0004725743,0.02093627,0.00196635,0.001079064,0.0004016697,0.0004987994,0.008408859,0.7254963,0.000775011,0.001415058,0.2246771],"study_design_scores_gemma":[0.0005759055,0.01234434,0.1223431,0.0004136113,0.002243206,0.005174435,0.0005082751,0.105798,0.7353606,0.002068163,0.01272883,0.0004414456],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8264831,0.01218478,0.1558079,0.0004310588,0.0003517274,0.0003534389,0.0008697851,0.001081341,0.002436914],"genre_scores_gemma":[0.7032226,0.007170838,0.2856579,0.0003720797,0.0001658991,0.000521064,0.001352052,0.0005610557,0.0009765689],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.004139647,"threshold_uncertainty_score":0.02189279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1452910595895228,"score_gpt":0.6089009224060595,"score_spread":0.4636098628165367,"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."}}