DORA cross-database EEG workload portability: supporting data, code and statistical methods

Supporting materials for “Target-independent verification of electroencephalography workload decoders for adaptive human–machine systems.” This dataset contains analysis code, software environment specifications, a public pre-target analytical specification, complete model-selection traces, non-identifying UNIVERSE prediction scores, participant-level AUC summaries, aggregate statistical results, diagnostics, generated figures, and machine-readable tables for a seven-database EEG workload portability audit. Four controlled-workload databases (RITHM, EEGMAT, COG-PBCI and STEW) supplied development evidence; UNIVERSE supplied untouched external confirmation; MultiPhysio-HRC and SenseCobot supplied joint environment-and-reported-effort stress tests. Third-party raw EEG archives and participant-level derived feature matrices are excluded. Source accessions and licenses are listed in data_sources.tsv. Original package materials are licensed under CC BY 4.0; analysis code is additionally licensed under the MIT License. Version 2 aligns the record and documentation with the current Engineering Applications of Artificial Intelligence submission. Scientific data, analysis code, results, predictions, figures and statistical methods are unchanged from Version 1. The canonical prediction file SHA-256 remains d3be68bf4efa9bd7ef5d72e6bd8604cbbb0dc1ba42cbf935fb34f6dae3df827c.《面向自适应人机系统的脑电图（electroencephalography，EEG）工作负荷解码器的目标无关验证》配套支撑材料。本数据集涵盖针对7个数据库的脑电图工作负荷可移植性审核所需的各类文件：分析代码、软件环境规范、公开预目标分析规范、完整模型选择轨迹、非识别性UNIVERSE预测分数、参与者级受试者工作特征曲线下面积（Area Under the ROC Curve，AUC）汇总结果、聚合统计结果、诊断分析报告、生成图表及机器可读表格。4个受控工作负荷数据库（RITHM、EEGMAT、COG-PBCI及STEW）提供了开发验证所需的数据集；UNIVERSE数据库提供了未经过预处理的外部验证数据；MultiPhysio-HRC与SenseCobot则提供了联合环境与自报负荷的压力测试数据集。第三方原始脑电图存档及参与者级衍生特征矩阵未纳入本数据集。数据源获取途径与授权协议详见data_sources.tsv文件。本数据集原始打包材料采用知识共享署名4.0（CC BY 4.0）协议授权；分析代码额外采用MIT许可证授权。V2版本将数据集记录与文档更新至当前投稿于《工程应用人工智能（Engineering Applications of Artificial Intelligence）》的稿件版本。科学数据、分析代码、计算结果、预测值、图表及统计方法均与V1版本完全一致。标准预测文件的安全哈希算法256（Secure Hash Algorithm 256，SHA-256）哈希值仍为d3be68bf4efa9bd7ef5d72e6bd8604cbbb0dc1ba42cbf935fb34f6dae3df827c。