{"id":"W4230964735","doi":"10.31224/osf.io/um762","title":"Quantification of Mental Stress using fNIRS Signals","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Functional near-infrared spectroscopy; Mental arithmetic; Prefrontal cortex; Psychology; Mental stress; Stress (linguistics); Task (project management); Cognitive psychology; Functional magnetic resonance imaging; Audiology; Cognition; Neuroscience; Medicine; Blood pressure","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001494183,0.00013944,0.0004001371,0.000135309,0.00001410699,0.00001905641,0.00009178811,0.0001596771,0.0002181588],"category_scores_gemma":[0.00003090966,0.0001155077,0.0001220421,0.00005790449,0.0000701352,0.00002509626,0.000133931,0.0002923839,0.00001095887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007671032,"about_ca_system_score_gemma":0.0001077955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002472292,"about_ca_topic_score_gemma":9.782166e-7,"domain_scores_codex":[0.9990354,0.00002282145,0.0003040725,0.000279847,0.0002292544,0.0001285779],"domain_scores_gemma":[0.9991987,0.00002583742,0.0001415537,0.0004661125,0.0001169399,0.00005080638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007937489,0.0003949762,0.01620684,0.0009104643,0.0001405896,0.000003634516,0.0001352263,0.000204333,0.9776718,0.001886977,0.001400471,0.0009653295],"study_design_scores_gemma":[0.0001780773,0.00009367859,0.001262386,0.001061825,0.0001390334,0.00000475456,0.00008782715,0.03295907,0.9636002,0.0004015045,0.00007177598,0.0001398239],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8794731,0.0003322155,0.09409684,0.0007738687,0.0003434631,0.001021422,0.00007100942,0.0002672921,0.02362079],"genre_scores_gemma":[0.9493418,0.00007266881,0.04931604,0.00005842142,0.00004620909,0.000005644771,0.0001120018,0.00002039099,0.001026782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06986874,"threshold_uncertainty_score":0.4710268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05800696935987844,"score_gpt":0.3941153488911138,"score_spread":0.3361083795312353,"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."}}