{"id":"W2156127840","doi":"10.1016/j.neuroimage.2005.05.014","title":"Flow-based fiber tracking with diffusion tensor and q-ball data: Validation and comparison to principal diffusion direction techniques","year":2005,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":173,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill Genome Centre; McGill University Health Centre; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Diffusion MRI; Imaging phantom; Anisotropic diffusion; Tracking (education); Anisotropy; Tensor (intrinsic definition); Fiber; Diffusion; Computer science; Computer vision; Artificial intelligence; Physics; Mathematics; Geometry; Optics; Materials science","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":[0.01503529,0.00118587,0.001353226,0.00312301,0.0011706,0.001708538,0.001290232,0.002289935,0.001517129],"category_scores_gemma":[0.0378572,0.0007207223,0.001037394,0.002041487,0.001074066,0.003254308,0.00177134,0.001470893,0.0009757589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006168225,"about_ca_system_score_gemma":0.002283795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0125972,"about_ca_topic_score_gemma":0.008794001,"domain_scores_codex":[0.9972459,0.001387165,0.0002270453,0.0005375534,0.0005028332,0.00009949638],"domain_scores_gemma":[0.9757231,0.01411854,0.001629694,0.002730686,0.005411231,0.0003867304],"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":[0.006684543,0.001361397,0.03972375,0.001961066,0.00168982,0.0003044655,0.001602256,0.161732,0.07594901,0.004153035,0.002808051,0.7020306],"study_design_scores_gemma":[0.0005185177,0.0009292961,0.01918795,0.0001700885,0.0005781852,0.0007520015,0.0001865413,0.94194,0.0298853,0.003215685,0.002478331,0.0001579947],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3263617,0.00174798,0.6670467,0.0002389649,0.0001936722,0.0004441366,0.0008414148,0.002028869,0.001096556],"genre_scores_gemma":[0.5776637,0.001327887,0.4169323,0.0001162467,0.00006357797,0.00028373,0.001166519,0.0008512973,0.001594788],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01503529,"threshold_uncertainty_score":0.07951516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07984183456497795,"score_gpt":0.3637643607038004,"score_spread":0.2839225261388225,"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."}}