{"id":"W4283013740","doi":"10.31222/osf.io/4nvpt","title":"EEG and ERP Methods - Preregistration Template","year":2022,"lang":"en","type":"preprint","venue":"","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Western Hospital; University of Toronto; University Health Network","funders":"","keywords":"Electroencephalography; Event-related potential; Event (particle physics); Computer science; Wish; Space (punctuation); Psychology; Sociology; Neuroscience; Physics","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":[0.003260115,0.001672438,0.000781315,0.001801758,0.0006309355,0.002100441,0.001591859,0.001569648,0.06791702],"category_scores_gemma":[0.02264675,0.001022264,0.001100439,0.002145801,0.0004792533,0.001800801,0.00167066,0.001795899,0.05359245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002995618,"about_ca_system_score_gemma":0.001348875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007713267,"about_ca_topic_score_gemma":0.001378834,"domain_scores_codex":[0.9986235,0.0003431064,0.0002253005,0.0002760334,0.0004440341,0.0000879997],"domain_scores_gemma":[0.9927937,0.002328723,0.0003316095,0.002253173,0.002140583,0.0001522267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008923577,0.0001766003,0.001600911,0.001329818,0.0001276531,0.0007741959,0.0007921213,0.005113223,0.07134277,0.03225228,0.1689653,0.7166328],"study_design_scores_gemma":[0.0002753105,0.0004405641,0.01313357,0.0003100713,0.000166695,0.004436618,0.0005925882,0.04096893,0.1436439,0.04850066,0.7472546,0.0002766528],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"protocol","genre_scores_codex":[0.00187382,0.0002545604,0.9782072,0.0002398323,0.0004866408,0.0005934741,0.00241592,0.009693333,0.006235249],"genre_scores_gemma":[0.01684712,0.0005561398,0.9435926,0.0003803131,0.000275959,0.003739888,0.006561014,0.01061464,0.01743234],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.06791702,"threshold_uncertainty_score":0.227205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09346827095345348,"score_gpt":0.3943201817596239,"score_spread":0.3008519108061705,"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."}}