{"id":"W4414552695","doi":"10.20944/preprints202509.2116.v1","title":"Automated Sleep Spindle Analysis in Epilepsy EEG Using Deep Learning","year":2025,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministero dello Sviluppo Economico","keywords":"Deep learning; Electroencephalography; Epilepsy; Sleep spindle; Sleep (system call); Convolutional neural network; Segmentation; Sleep Stages","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004715568,0.000747982,0.0003338617,0.0009577843,0.0001390903,0.0004042467,0.0004432512,0.0003738591,0.0008563041],"category_scores_gemma":[0.001307002,0.0001936495,0.0004456135,0.0004710139,0.0001478224,0.000384134,0.0005922192,0.0004310269,0.0004503076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002741719,"about_ca_system_score_gemma":0.0004225989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006390397,"about_ca_topic_score_gemma":0.009926718,"domain_scores_codex":[0.99983,0.00004494757,0.00001174585,0.00005488164,0.00003089363,0.00002751549],"domain_scores_gemma":[0.9997627,0.00009746891,0.00003860697,0.00003363582,0.00005234907,0.00001526227],"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":[0.0006299131,0.000288923,0.02263035,0.0002981275,0.0002365443,0.0003885018,0.0001624398,0.1774052,0.0609544,0.001165369,0.006143705,0.7296965],"study_design_scores_gemma":[0.00001975226,0.0000632935,0.00828665,0.00002009627,0.00002146801,0.00008713038,0.00002926881,0.9813671,0.008468852,0.000879874,0.0007458441,0.00001063517],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.415917,0.002057401,0.5690668,0.0003712568,0.00006956589,0.0001418474,0.001758727,0.008593507,0.002023842],"genre_scores_gemma":[0.9045476,0.0004607768,0.08988344,0.00008404912,0.00003605302,0.00008803493,0.003179472,0.0001098298,0.001610729],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006390397,"threshold_uncertainty_score":0.0127064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1031092254586794,"score_gpt":0.3683268975361874,"score_spread":0.265217672077508,"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."}}