{"id":"W4414357448","doi":"10.1101/2025.09.16.676602","title":"sEEG-Suite: An Interactive Pipeline for Semi-Automated Contact Localization and Anatomical Labeling with Brainstorm","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Congressionally Directed Medical Research Programs; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institutes of Health; U.S. Department of Defense","keywords":"Stereoelectroencephalography; Pipeline (software); Brainstorming; Software; Automation; Visualization; Segmentation; Image segmentation; Image processing","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":[],"consensus_categories":[],"category_scores_codex":[0.002094202,0.003215787,0.001776204,0.003144526,0.001150485,0.002862659,0.003930771,0.002059724,0.1639373],"category_scores_gemma":[0.005335519,0.001960306,0.002271364,0.001282409,0.0005801028,0.001983377,0.003379442,0.003159827,0.1049755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007775816,"about_ca_system_score_gemma":0.002486523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005330107,"about_ca_topic_score_gemma":0.01524591,"domain_scores_codex":[0.9994168,0.00009203054,0.00005432501,0.000144139,0.0002113418,0.00008128726],"domain_scores_gemma":[0.9986914,0.0006128727,0.00007466238,0.0002734023,0.0002431083,0.0001045478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002616285,0.00003983658,0.00055498,0.001309925,0.0003000029,0.0002266263,0.0003049879,0.001552784,0.01199166,0.003148685,0.9021513,0.07815759],"study_design_scores_gemma":[0.0006794021,0.0001306085,0.007441399,0.000547245,0.0003773657,0.002597949,0.0004011439,0.07608073,0.04325055,0.0595674,0.8083659,0.0005602343],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.002619146,0.000768163,0.3470618,0.0005307957,0.0003812321,0.0004116747,0.07927644,0.5634985,0.005452218],"genre_scores_gemma":[0.02389867,0.001090993,0.6072888,0.000904531,0.0002057066,0.003305721,0.114186,0.234356,0.01476342],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.1639373,"threshold_uncertainty_score":0.5484251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01593565111118534,"score_gpt":0.2634818165915904,"score_spread":0.247546165480405,"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."}}