{"id":"W4412166743","doi":"10.1017/cjn.2025.10310","title":"P.165 Comparison of preoperative diffusion tensor imaging tractography platforms for intrinsic brain lesions","year":2025,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Hospital Edmonton; Workers Compensation Board of Alberta","funders":"","keywords":"Diffusion MRI; Tractography; Medicine; Neuroscience; Nuclear magnetic resonance; Radiology; Psychology; Magnetic resonance imaging; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.002777881,0.0004126789,0.000294134,0.001649158,0.0002697964,0.0007731786,0.0003125178,0.0002582028,0.005287305],"category_scores_gemma":[0.01207712,0.0001826971,0.0006866993,0.0006832754,0.000404145,0.0009078277,0.0007314807,0.00029663,0.001185709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003473226,"about_ca_system_score_gemma":0.0004655427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005955674,"about_ca_topic_score_gemma":0.0008021914,"domain_scores_codex":[0.9989109,0.000261712,0.0002631867,0.0001602184,0.0003060447,0.00009796619],"domain_scores_gemma":[0.9905612,0.004395948,0.002183403,0.0005795675,0.001753489,0.0005264512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00462331,0.0001385666,0.9233571,0.0001895681,0.0002184718,0.0004070069,0.0003773713,0.0007011725,0.00430944,0.0001041168,0.0004460017,0.06512786],"study_design_scores_gemma":[0.00008357834,0.006688477,0.9796679,0.00008975322,0.0002280728,0.003325479,0.0004647647,0.003052311,0.004965735,0.0002018125,0.001199035,0.00003303953],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963514,0.0004227743,0.001849346,0.00002016676,0.00001524813,0.0000473281,0.0003407665,0.00002944899,0.0009235716],"genre_scores_gemma":[0.9978361,0.0001005909,0.001390839,0.000007541307,0.0000130215,0.00004241595,0.0004389496,0.00001928944,0.0001513114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005287305,"threshold_uncertainty_score":0.01768786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.073518601362403,"score_gpt":0.3690019808808544,"score_spread":0.2954833795184514,"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."}}