{"id":"W4396860186","doi":"10.1007/s42154-023-00252-1","title":"Prefrontal Correlates of Passengers’ Mental Activity Based on fNIRS for High-Level Automated Vehicles","year":2024,"lang":"en","type":"article","venue":"Automotive Innovation","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Psychology; Prefrontal cortex; Computer science; Cognitive psychology; Neuroscience; Cognition","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004082382,0.0001930895,0.0002178853,0.0005657181,0.0001134046,0.0000453714,0.0001004024,0.0001869567,0.001291291],"category_scores_gemma":[0.0001437214,0.0001849108,0.00008561734,0.0007335382,0.00007396358,0.0002683724,0.0000148891,0.0002381283,0.0002244551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002248088,"about_ca_system_score_gemma":0.00007771508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005606079,"about_ca_topic_score_gemma":0.00001047008,"domain_scores_codex":[0.9985836,0.000129275,0.0004753206,0.0003756943,0.0002343006,0.0002018361],"domain_scores_gemma":[0.9986767,0.0004851957,0.0002361699,0.0002086531,0.0003673045,0.00002593738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.002734187,0.00308183,0.00436302,0.0004963204,0.00145639,0.00002792604,0.01805478,0.00128949,0.1445606,0.5147909,0.1489174,0.1602271],"study_design_scores_gemma":[0.002189445,0.0008938378,0.6116371,0.0002781369,0.00005554834,0.000007148575,0.0008007914,0.3338858,0.04464751,0.001045148,0.004180239,0.0003792504],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9718843,0.00001017307,0.015498,0.001335117,0.003472612,0.0006954062,0.0004925418,0.001125923,0.005485928],"genre_scores_gemma":[0.9970246,5.112354e-7,0.0004607748,0.000239588,0.0000917299,0.0001459976,0.000448749,0.00003675328,0.001551329],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6072741,"threshold_uncertainty_score":0.9996217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04738177164772572,"score_gpt":0.3671165796059306,"score_spread":0.3197348079582049,"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."}}