{"id":"W4390703067","doi":"10.14293/pr2199.000609.v2","title":"Electroencephalogram-Based Human Performance Analysis for Improved Small Modular Reactor Operation","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada; University of Ontario Institute of Technology","keywords":"Modular design; Electroencephalography; Interfacing; Software deployment; Computer science; SAFER; Reliability (semiconductor); Human reliability; Control (management); Human error; Systems engineering; Risk analysis (engineering); Simulation; Human–computer interaction; Reliability engineering; Power (physics); Artificial intelligence; Engineering; Psychology; Software engineering; Computer hardware; Neuroscience; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000332701,0.0005098811,0.0002133801,0.0004881576,0.00007357015,0.0004827116,0.0002200902,0.0002547027,0.0012884],"category_scores_gemma":[0.001740878,0.00008696172,0.0001834155,0.0004142438,0.0001745898,0.0004194347,0.0003954966,0.0002487046,0.0002167027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001271571,"about_ca_system_score_gemma":0.0001974678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008533635,"about_ca_topic_score_gemma":0.001340523,"domain_scores_codex":[0.9998304,0.00006631928,0.000007983144,0.00003690397,0.00004611386,0.00001228667],"domain_scores_gemma":[0.9996706,0.0001549707,0.00006467894,0.00004024357,0.00005186682,0.0000175748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00106062,0.0003352558,0.03508417,0.0007356377,0.000164406,0.0005482018,0.0008817614,0.1033335,0.2993618,0.002570827,0.0017095,0.5542143],"study_design_scores_gemma":[0.00007101355,0.001157135,0.1888971,0.0001370652,0.0001644419,0.0007160428,0.0007705953,0.724857,0.07167095,0.007267059,0.004183842,0.0001077016],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5705898,0.000574636,0.4233717,0.0002238396,0.0000434996,0.0001215531,0.0006311953,0.0007507449,0.003693045],"genre_scores_gemma":[0.9527229,0.0003461135,0.04618696,0.00002204209,0.00002501324,0.00003550212,0.0002172037,0.00003148543,0.0004127887],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0012884,"threshold_uncertainty_score":0.004310191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1064124541500739,"score_gpt":0.3788547704336239,"score_spread":0.27244231628355,"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."}}