{"id":"W4414945900","doi":"10.1088/1741-2552/ae10e0","title":"PyHFO 2.0: an open-source platform for deep learning—based clinical high-frequency oscillations analysis","year":2025,"lang":"en","type":"article","venue":"Journal of Neural Engineering","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke","keywords":"Scalability; Bridging (networking); Set (abstract data type); Artifact (error); Identification (biology); Electroencephalography; Deep learning; Computational model; Neuroinformatics","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":[0.002040527,0.001760436,0.0007489899,0.001177225,0.000368841,0.001235533,0.003012961,0.0007102168,0.02677229],"category_scores_gemma":[0.00670643,0.0007866386,0.00133014,0.0005349253,0.0008064758,0.001427559,0.00379975,0.00185191,0.008857559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005291337,"about_ca_system_score_gemma":0.003137987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002659797,"about_ca_topic_score_gemma":0.003216772,"domain_scores_codex":[0.9994081,0.00008898418,0.00004930551,0.0001694579,0.00020279,0.00008138964],"domain_scores_gemma":[0.9987112,0.0004925328,0.0001862812,0.0001901582,0.0002261771,0.0001935411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00490739,0.0005591701,0.01434391,0.003764134,0.0008909946,0.001404734,0.0007736952,0.04884107,0.02973882,0.01368677,0.4563444,0.4247449],"study_design_scores_gemma":[0.001935503,0.0006843043,0.02190012,0.0008445285,0.0003680561,0.00216175,0.0001493364,0.6161959,0.07132131,0.06344614,0.220296,0.0006971052],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.01977302,0.0006365426,0.5208454,0.001200451,0.0004060793,0.0009063563,0.02930026,0.4217418,0.005190164],"genre_scores_gemma":[0.2941822,0.001333114,0.5212018,0.003144791,0.0003940352,0.005313342,0.06087302,0.09724303,0.01631479],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.02677229,"threshold_uncertainty_score":0.08956224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05000239853857221,"score_gpt":0.3428558893873575,"score_spread":0.2928534908487853,"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."}}