{"id":"W4386252129","doi":"10.1111/ejn.16135","title":"Effect of number of diffusion encoding directions in neonatal diffusion tensor imaging using Tract‐Based Spatial Statistical analysis","year":2023,"lang":"en","type":"article","venue":"European Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Turun Yliopistosäätiö; Turun Yliopistollinen Keskussairaala; Emil Aaltosen Säätiö; Signe ja Ane Gyllenbergin Säätiö; Jane ja Aatos Erkon Säätiö; Academy of Finland; Varsinais-Suomen Sairaanhoitopiiri; Alfred Kordelinin Säätiö","keywords":"Diffusion MRI; Diffusion; Encoding (memory); Statistical physics; Neuroscience; Computer science; Medicine; Physics; Biology; Radiology; Magnetic resonance imaging","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":[0.01533778,0.0008450114,0.001147181,0.0006480758,0.0003660865,0.001055547,0.000493562,0.0005929569,0.0009931339],"category_scores_gemma":[0.06755967,0.0004407027,0.001134973,0.0006850727,0.0007332611,0.001061286,0.0008053734,0.0009246665,0.0002163397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004879422,"about_ca_system_score_gemma":0.001066304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002120606,"about_ca_topic_score_gemma":0.002488423,"domain_scores_codex":[0.9908808,0.005773803,0.001035718,0.001051485,0.001086865,0.0001713627],"domain_scores_gemma":[0.9389587,0.04786401,0.005465272,0.00407537,0.002597263,0.001039435],"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":[0.05258309,0.0013229,0.2667336,0.001508565,0.004094135,0.002272971,0.001884386,0.06405274,0.2479576,0.00157646,0.001506343,0.3545072],"study_design_scores_gemma":[0.0006952905,0.02864652,0.5533553,0.0006216107,0.004832066,0.003629266,0.0006753276,0.2524399,0.1446013,0.003377599,0.00663771,0.0004880234],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9479237,0.00320188,0.04720382,0.0002914288,0.000173323,0.00008773265,0.0002395388,0.0002931104,0.0005854711],"genre_scores_gemma":[0.9493486,0.001071028,0.04820318,0.00008717129,0.00006025506,0.0001656977,0.0003324301,0.0003320308,0.0003996262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01533778,"threshold_uncertainty_score":0.08111489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04305764631367952,"score_gpt":0.3744289100689669,"score_spread":0.3313712637552874,"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."}}