{"id":"W4416726489","doi":"10.1109/mwscas53549.2025.11244460","title":"Enhancing Pulse Oximetry Accuracy with Personal Parameter Integration in Wearable Devices","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":"Algonquin College","funders":"National Institutes of Health; National Science Foundation","keywords":"Pulse oximetry; Wearable computer; Photoplethysmogram; Oxygen saturation; Artificial neural network; Calibration; Key (lock); Computation","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004146307,0.0005504219,0.0005163847,0.0007337439,0.0001454219,0.0004109296,0.0003031259,0.0002712829,0.0005313454],"category_scores_gemma":[0.0004898668,0.0005030882,0.0001150442,0.001784299,0.00006617566,0.001372311,0.0001154828,0.0008595669,0.0001210938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006621606,"about_ca_system_score_gemma":0.0001490273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009836484,"about_ca_topic_score_gemma":0.002201151,"domain_scores_codex":[0.9973985,0.00009399356,0.0006907324,0.0006446979,0.0003698162,0.0008022579],"domain_scores_gemma":[0.9981903,0.001103947,0.00009513204,0.0003478579,0.0001300726,0.0001326961],"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":[0.0002368063,0.0002664517,0.1561765,0.00128092,0.0003875861,0.0001014968,0.002691305,0.003261419,0.7021599,0.0006397432,0.0000687288,0.1327291],"study_design_scores_gemma":[0.001224245,0.0001864308,0.01636039,0.004867395,0.0001092637,0.00001055466,0.004911202,0.02039909,0.9506531,0.0003007379,0.0001274075,0.0008501696],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8124105,0.002931664,0.1667091,0.0001464371,0.001026532,0.0005897021,0.000003836346,0.0001741402,0.01600803],"genre_scores_gemma":[0.9846354,0.0001409052,0.01377667,0.0001125109,0.0001896514,0.00007175859,0.000004657525,0.00006126562,0.001007191],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2484931,"threshold_uncertainty_score":0.9997421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01097587397824648,"score_gpt":0.2483884977030652,"score_spread":0.2374126237248187,"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."}}