{"id":"W4402745651","doi":"10.1101/2024.09.19.612894","title":"<i>SMART MRS</i> : A Simulated MEGA-PRESS Artifacts Toolbox for GABA-edited MRS","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Children's Hospital Research Institute; Alberta Innovates","keywords":"Toolbox; Mega-; Computer science; Physics; Programming language","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":[0.001415344,0.001402291,0.0005938562,0.000613597,0.0004824039,0.001069338,0.003787535,0.0009784638,0.03995609],"category_scores_gemma":[0.003153296,0.0007000223,0.00104365,0.0004016613,0.0006893024,0.001019016,0.001955744,0.001588899,0.01262806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005612754,"about_ca_system_score_gemma":0.001251906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001403658,"about_ca_topic_score_gemma":0.001692113,"domain_scores_codex":[0.9995565,0.0001022745,0.0000382519,0.00007082713,0.0001686821,0.00006345149],"domain_scores_gemma":[0.9988081,0.000395796,0.0001477764,0.0002378073,0.0002663666,0.0001441706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00256755,0.0004626675,0.007672105,0.00221152,0.0005605329,0.002855179,0.001128735,0.2501977,0.1229595,0.03624072,0.3438058,0.229338],"study_design_scores_gemma":[0.0002988164,0.0002214671,0.002149256,0.0001403298,0.00006711767,0.001261351,0.00004918903,0.7066954,0.1326046,0.01352511,0.1427959,0.0001914497],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.01532404,0.00008838477,0.7937039,0.0003512652,0.0001844857,0.0002267698,0.005484754,0.1770693,0.00756712],"genre_scores_gemma":[0.1486862,0.0002563954,0.7312152,0.0008581693,0.0001163719,0.001356538,0.01160546,0.08930324,0.01660245],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.03995609,"threshold_uncertainty_score":0.1336665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02529082813071754,"score_gpt":0.2835396264430593,"score_spread":0.2582487983123418,"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."}}