{"id":"W4309679519","doi":"10.1109/smc53654.2022.9945250","title":"Activity Ratio to Measure Physical Demand of Cognitive Workload","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Alberta Innovates","keywords":"Workload; Measure (data warehouse); Computer science; Cognition; Psychology; Data mining; Operating system","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":[0.001078725,0.0009456096,0.0004713381,0.001546072,0.0002146369,0.0008430572,0.0005764582,0.0007034725,0.005286093],"category_scores_gemma":[0.006259296,0.0001811621,0.0005807148,0.00113498,0.0002699243,0.000747329,0.0006383255,0.0007281919,0.00143351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000231762,"about_ca_system_score_gemma":0.0002145287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007357951,"about_ca_topic_score_gemma":0.001466882,"domain_scores_codex":[0.9985538,0.0003606329,0.0001938533,0.0002449299,0.000540109,0.0001066653],"domain_scores_gemma":[0.9966477,0.001367972,0.0007656688,0.0001897348,0.0007753361,0.000253677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002534283,0.002659003,0.543566,0.002724335,0.00121128,0.0006477671,0.002079608,0.006226994,0.09652987,0.004227242,0.009020777,0.3285728],"study_design_scores_gemma":[0.0001354755,0.004279024,0.9477108,0.0002192367,0.0003793287,0.001416368,0.001375914,0.01549296,0.01575015,0.002967478,0.01010404,0.0001693464],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8590192,0.002844298,0.1023699,0.0004263187,0.0005130501,0.001417931,0.006060103,0.0008446135,0.02650453],"genre_scores_gemma":[0.9632896,0.0009287735,0.02685653,0.0002819834,0.0002050499,0.001253581,0.002780506,0.00007502822,0.004328905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005286093,"threshold_uncertainty_score":0.01768374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07856786339092965,"score_gpt":0.3703474229794786,"score_spread":0.291779559588549,"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."}}