{"id":"W2620311529","doi":"10.1002/hbm.23658","title":"White matter microstructure in athletes with a history of concussion: Comparing diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI)","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":108,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto; St. Michael's Hospital","funders":"Canadian Institutes of Health Research; Siemens Canada; Canadian Institute for Military and Veteran Health Research; Defence Research and Development Canada","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Concussion; Athletes; Magnetic resonance imaging; Psychology; Neurite; Neuroscience; Medicine; Chemistry; Physical therapy; Poison control; Radiology; Injury prevention","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":[0.0004246997,0.0003043207,0.0003132017,0.001063465,0.0004672305,0.0004841972,0.0001916676,0.0005381692,0.0009340116],"category_scores_gemma":[0.001240062,0.0002185765,0.0002267023,0.0004482288,0.0003684061,0.0003715167,0.0005092871,0.0002148339,0.0001968647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003012961,"about_ca_system_score_gemma":0.0002206125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005647108,"about_ca_topic_score_gemma":0.006128483,"domain_scores_codex":[0.9997792,0.00003121427,0.00003131343,0.00005647658,0.00003660359,0.00006518983],"domain_scores_gemma":[0.9993819,0.00006946865,0.0002800249,0.00002422964,0.00009571591,0.0001487319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003522151,0.00006205624,0.9964015,0.00001213679,0.0000369551,0.0001952607,0.0002451047,0.00002713809,0.001041432,0.00001014233,0.00002422431,0.001591775],"study_design_scores_gemma":[0.000004476211,0.0002495926,0.9987722,0.000004682871,0.00001457208,0.0003417134,0.0003650297,0.00008408266,0.000109247,0.00000787019,0.00004415557,0.00000226857],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998118,0.0000494518,0.00002313506,0.000005335764,0.000001758458,0.000004101992,0.00002974501,6.644948e-7,0.00007387745],"genre_scores_gemma":[0.9997414,0.00003669864,0.00005231886,0.000006859757,0.000007222526,0.000004459661,0.00006963807,6.300917e-7,0.00008077425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005647108,"threshold_uncertainty_score":0.0112285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03303363302585623,"score_gpt":0.2934358046874379,"score_spread":0.2604021716615817,"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."}}