{"id":"W2950396589","doi":"10.1016/j.dcn.2017.12.002","title":"Diffusion MRI of white matter microstructure development in childhood and adolescence: Methods, challenges and progress","year":2017,"lang":"en","type":"review","venue":"Developmental Cognitive Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":171,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"National Institute for Health and Care Research","keywords":"Diffusion MRI; Neuroimaging; Psychology; White matter; Brain development; Popularity; Data science; Neuroscience; Cognitive psychology; Magnetic resonance imaging; Computer science; Medicine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002240452,0.0003860293,0.0009446335,0.0002563032,0.0002693964,0.00003095215,0.0002196224,0.0001273678,0.00000300073],"category_scores_gemma":[0.0001036806,0.0003091653,0.00005174062,0.0001743686,0.0007221234,0.0001155074,0.0007179212,0.0004303052,0.000001618943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000435253,"about_ca_system_score_gemma":0.0002529451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.800102e-7,"about_ca_topic_score_gemma":0.000001170344,"domain_scores_codex":[0.9980556,0.00008415119,0.0004818225,0.0008872731,0.0002110108,0.0002800946],"domain_scores_gemma":[0.999156,0.00006759883,0.0003915855,0.0001966443,0.0000650922,0.000123063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000006938147,0.00008948877,0.009661344,0.003305235,0.000004200872,0.00002266504,0.0005115789,1.062263e-9,0.00006832066,0.000009928456,0.000003468029,0.9863169],"study_design_scores_gemma":[0.0004287481,0.00006498784,0.7563774,0.02334229,0.00008929925,0.00109261,0.0000724366,0.000001567801,0.0003164306,0.00005327227,0.2177338,0.0004272017],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00296324,0.9940389,0.0004245012,0.000150821,0.00006159316,0.00201793,0.00003670112,0.00004051536,0.0002657858],"genre_scores_gemma":[0.002245028,0.9447166,0.05251504,0.0001884815,0.00001082273,0.0001895039,0.00002298374,0.0000357477,0.00007577197],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9858896,"threshold_uncertainty_score":0.999936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1406222692049797,"score_gpt":0.4381496966508886,"score_spread":0.2975274274459089,"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."}}