{"id":"W4416249896","doi":"10.1109/ijcnn64981.2025.11227277","title":"Designing Stress Response Analyzer using Composite Cardiovascular Biomarkers","year":2025,"lang":"","type":"article","venue":"","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Workload; Wearable computer; Stress (linguistics); Composite number; Spectrum analyzer; Ranging; Accelerometer","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008825185,0.001068614,0.0007928605,0.00090973,0.0002233712,0.0009548904,0.0008812866,0.000876595,0.001421389],"category_scores_gemma":[0.001850812,0.0003857145,0.0004156933,0.0005730857,0.0002630552,0.0008721605,0.000593373,0.0004982171,0.0007947437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001404587,"about_ca_system_score_gemma":0.0003686959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002425606,"about_ca_topic_score_gemma":0.0005441653,"domain_scores_codex":[0.9992817,0.000158362,0.00005013961,0.0002538867,0.000206293,0.00004954469],"domain_scores_gemma":[0.9991019,0.0003757128,0.0001072485,0.00007308503,0.0002700885,0.0000720777],"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":[0.002114118,0.0004816358,0.01898658,0.0007955799,0.0002824258,0.0004726878,0.0002351423,0.004055989,0.660915,0.001389866,0.00218947,0.3080815],"study_design_scores_gemma":[0.0003295549,0.005948959,0.05043603,0.0001777876,0.0008486904,0.004348493,0.0002715026,0.2603796,0.6570113,0.003924713,0.01609605,0.000227244],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1207024,0.0008898071,0.8742623,0.0002399877,0.000312576,0.0003797741,0.000291878,0.001698187,0.001223047],"genre_scores_gemma":[0.4675025,0.00106544,0.5265675,0.0006080783,0.0004082354,0.0006364606,0.0003106216,0.0001172333,0.002784051],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001421389,"threshold_uncertainty_score":0.00475502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01725529864558859,"score_gpt":0.2488585935743702,"score_spread":0.2316032949287816,"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."}}