{"id":"W2791341284","doi":"10.1016/j.bbr.2018.03.025","title":"STATSLAB: An open-source EEG toolbox for computing single-subject effects using robust statistics","year":2018,"lang":"en","type":"article","venue":"Behavioural Brain Research","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"Brock University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Toolbox; Normality; Computer science; Robust statistics; Statistical hypothesis testing; Truncated mean; Statistics; Percentile; Range (aeronautics); Electroencephalography; Artificial intelligence; Data mining; Mathematics; Psychology; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004896524,0.0003152217,0.0005535042,0.0001994804,0.001112966,0.000512188,0.000884884,0.0001709566,0.0000751654],"category_scores_gemma":[0.01062175,0.0002918292,0.00005960494,0.0004288926,0.0004849846,0.0003767875,0.0005915121,0.000571222,0.00001132079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002814234,"about_ca_system_score_gemma":0.0001951839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003687841,"about_ca_topic_score_gemma":0.0002013813,"domain_scores_codex":[0.9950896,0.001361982,0.0005830026,0.0007921031,0.00083334,0.00133996],"domain_scores_gemma":[0.9838082,0.01379101,0.0001675583,0.0006875457,0.001121856,0.0004237975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001049502,0.002073801,0.0009462382,0.000980944,0.0001062307,0.0001709264,0.003996724,0.0004249796,0.09036481,0.3461066,0.01757805,0.5362012],"study_design_scores_gemma":[0.004538249,0.008674265,0.001619282,0.0006508933,0.0001587135,0.0000679313,0.001435414,0.4027201,0.01575619,0.5609573,0.001995761,0.001425884],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1824003,0.00001432502,0.8148347,0.000117275,0.0001732833,0.001848844,0.0002892669,0.00009738295,0.0002245772],"genre_scores_gemma":[0.1924527,6.493504e-7,0.8060933,0.0001132798,0.0002153153,0.00005351641,0.00004803182,0.0001303438,0.0008928094],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5347753,"threshold_uncertainty_score":0.9999534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5972846182606136,"score_gpt":0.56733554259886,"score_spread":0.02994907566175364,"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."}}