{"id":"W4407168549","doi":"10.1109/lra.2025.3539103","title":"Quantifying Human Mental State in Interactive pHRI: Maintaining Balancing","year":2025,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Research Council","keywords":"State (computer science); Mental state; Computer science; Human–computer interaction; Psychology; Process management; Business; Applied psychology","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":[0.0003355767,0.0002860223,0.0001617594,0.0002073067,0.0001502506,0.0005304127,0.0001549017,0.0002522396,0.001431748],"category_scores_gemma":[0.00308601,0.0001146566,0.0001251593,0.0001234608,0.0002717501,0.0003435782,0.0004446643,0.0001885325,0.0002359344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001120774,"about_ca_system_score_gemma":0.0000913925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007207151,"about_ca_topic_score_gemma":0.001318683,"domain_scores_codex":[0.9997861,0.00008286453,0.00001181138,0.00004656043,0.00005039691,0.00002225915],"domain_scores_gemma":[0.9994288,0.000260193,0.0001329103,0.00004629487,0.00007777592,0.000053892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.003166398,0.0008602976,0.3114501,0.0007767873,0.0002451227,0.0003831975,0.01223575,0.003758874,0.4579769,0.0006159,0.001005469,0.2075253],"study_design_scores_gemma":[0.00002830835,0.001419592,0.9627178,0.00003958694,0.00007744497,0.000360797,0.002783532,0.008591945,0.02246134,0.0005428356,0.0009199397,0.00005680636],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936624,0.00004759062,0.004976182,0.00002847517,0.000005253791,0.00003143122,0.00008312942,0.00003480738,0.001130928],"genre_scores_gemma":[0.997308,0.0000391534,0.002193642,0.00002414067,0.000004333409,0.00003371345,0.0000549243,0.000005623695,0.000336588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001431748,"threshold_uncertainty_score":0.00478965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02923871463433123,"score_gpt":0.3111385279413175,"score_spread":0.2818998133069863,"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."}}