{"id":"W2084775462","doi":"10.1109/tpami.2012.184","title":"3D Stochastic Completion Fields for Mapping Connectivity in Diffusion MRI","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Pattern Analysis and Machine Intelligence","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Spherical harmonics; Computer science; Artificial intelligence; Probability density function; Algorithm; Invariant (physics); Orientation (vector space); Imaging phantom; Computer vision; Mathematics; Geometry; Mathematical analysis; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001473113,0.0001243931,0.0002589919,0.0003296124,0.0001114873,0.00001069009,0.00004705465,0.00004817318,0.00006233797],"category_scores_gemma":[0.00000757951,0.0001115225,0.0001290362,0.0004152881,0.00003652768,0.0000671876,0.00000198824,0.0002032242,0.000003142988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003526888,"about_ca_system_score_gemma":0.000005116553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003153215,"about_ca_topic_score_gemma":0.0002681598,"domain_scores_codex":[0.9992286,0.00002253275,0.0002298912,0.0002400058,0.00009572205,0.0001832619],"domain_scores_gemma":[0.9994444,0.0001676956,0.00005740975,0.0002090121,0.00003605119,0.00008542531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001340315,0.001380706,0.03010187,0.000117189,0.0002582678,0.000002546269,0.0006458085,0.02381813,0.005101661,0.0001696146,0.00002034785,0.9382498],"study_design_scores_gemma":[0.000752603,0.0004277155,0.07843716,0.0002021519,0.001441822,0.00005322056,0.0001993575,0.855697,0.06066557,0.0008775924,0.0006693288,0.0005765235],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04735381,0.00004637938,0.9514006,0.000678694,0.00004535872,0.0003630435,0.00003536621,0.00005525952,0.0000215425],"genre_scores_gemma":[0.9954135,0.0001190322,0.003814593,0.0004244588,0.00002547364,0.0001227088,0.00001586222,0.00001105524,0.00005336259],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9480596,"threshold_uncertainty_score":0.4547755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06916264017012254,"score_gpt":0.3474442211282918,"score_spread":0.2782815809581692,"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."}}