{"id":"W4409905343","doi":"10.1007/s00429-025-02921-9","title":"The scientific value of tractography: accuracy vs usefulness","year":2025,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institutes of Health; Université de Bordeaux; Agence Nationale de la Recherche; European Commission; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Hope for Depression Research Foundation","keywords":"Tractography; Value (mathematics); Psychology; Computer science; Medical physics; Medicine; Diffusion MRI; Radiology; Machine learning; 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.2034983,0.001947843,0.004690692,0.01460699,0.001469184,0.01027971,0.003994383,0.008323863,0.004381093],"category_scores_gemma":[0.5451658,0.001490433,0.002024846,0.00666854,0.02310376,0.01917479,0.005353019,0.007508037,0.002023046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00290032,"about_ca_system_score_gemma":0.003455669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002173075,"about_ca_topic_score_gemma":0.002082958,"domain_scores_codex":[0.8627418,0.09013935,0.010726,0.008449182,0.02700499,0.0009387371],"domain_scores_gemma":[0.2083795,0.6805035,0.03091664,0.04699299,0.03101004,0.002197364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002831004,0.0002656697,0.2389285,0.00781248,0.009743917,0.001126892,0.003128971,0.01286842,0.003055667,0.1737413,0.02592292,0.5205743],"study_design_scores_gemma":[0.0005382149,0.0008135631,0.06350894,0.005767711,0.00317766,0.004961875,0.001810196,0.05845929,0.005247416,0.8051155,0.05008761,0.0005121274],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1097599,0.2756904,0.3391177,0.2185297,0.009070564,0.0003623629,0.002750221,0.0009970944,0.04372209],"genre_scores_gemma":[0.8380196,0.04911524,0.08053592,0.01201304,0.01633471,0.0002042752,0.0004331289,0.0006283195,0.002715757],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2034983,"threshold_uncertainty_score":0.9822284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02590243329021894,"score_gpt":0.3196066035403977,"score_spread":0.2937041702501787,"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."}}