{"id":"W4210591792","doi":"10.1002/nbm.4702","title":"Comparison of seven modelling algorithms for γ‐aminobutyric acid–edited proton magnetic resonance spectroscopy","year":2022,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; Wellcome Trust; Australian Research Council; National Institute on Aging; National Institutes of Health; European Research Council","keywords":"Algorithm; Computer science; Consistency (knowledge bases); Benchmark (surveying); Metabolite; Correlation; Artificial intelligence; Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000285935,0.0001462596,0.0004672727,0.0002928342,0.00009375394,0.000002180316,0.0001567472,0.00005870271,0.0001023482],"category_scores_gemma":[0.00002432859,0.0001354808,0.00005824714,0.0008621741,0.0001144813,0.00002751935,0.0000671005,0.0002823258,0.000001113225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001705916,"about_ca_system_score_gemma":0.00006210068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004010923,"about_ca_topic_score_gemma":0.000001541192,"domain_scores_codex":[0.9984931,0.00001994853,0.0005308118,0.0003242641,0.0003501746,0.0002816639],"domain_scores_gemma":[0.9992729,0.00006454597,0.0001596686,0.000343872,0.00008347196,0.0000755247],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003103956,0.005723351,0.03208456,0.001595157,0.0000378531,0.0000591764,0.004199945,0.01379393,0.718721,0.003743736,0.0165391,0.2003983],"study_design_scores_gemma":[0.005270632,0.006053241,0.00155041,0.000310519,0.0000995525,0.00004905522,0.001185741,0.5812242,0.1668454,0.003271659,0.2338219,0.000317615],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09157971,0.009075787,0.8869475,0.003919667,0.0001586435,0.007146505,0.0002123525,0.0002136414,0.0007462485],"genre_scores_gemma":[0.710856,0.0002096098,0.2845757,0.0002242649,0.0002281359,0.003075314,0.0002813344,0.00004306267,0.000506679],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6192762,"threshold_uncertainty_score":0.5524747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05767606667509703,"score_gpt":0.3949615157930068,"score_spread":0.3372854491179098,"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."}}