{"id":"W4416960545","doi":"10.1109/embc58623.2025.11253776","title":"Computational Analysis of Voice as Digital Biomarkers for Clinical Assessment for Distress in Female Cancer Patients","year":2025,"lang":"en","type":"article","venue":"","topic":"Cancer survivorship and care","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Distress; Cancer; Multivariate analysis; Correlation; Clinical Oncology; Multivariate statistics; Voice Disorder; Breast cancer","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006912898,0.0004044878,0.0004039619,0.0006391777,0.0001409809,0.0008304263,0.0002621071,0.0003746979,0.002750383],"category_scores_gemma":[0.003147651,0.0001490815,0.0007360405,0.0002419623,0.0001696042,0.0002911016,0.0004698967,0.0003460678,0.0005490114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002789358,"about_ca_system_score_gemma":0.0004106109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002824847,"about_ca_topic_score_gemma":0.003753653,"domain_scores_codex":[0.9997762,0.00009298784,0.00001498928,0.00004984777,0.0000411442,0.00002485103],"domain_scores_gemma":[0.9992493,0.0005840175,0.00005589681,0.00002625964,0.00005651861,0.0000281416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001988369,0.0003968693,0.2155194,0.0004652088,0.0005844036,0.0008715705,0.0005819282,0.3150047,0.02547273,0.002640717,0.005528249,0.4309458],"study_design_scores_gemma":[0.00002095791,0.0002591601,0.0648656,0.0000450828,0.00009481505,0.0002519132,0.0001874992,0.9293454,0.00193401,0.001783655,0.001182542,0.00002936348],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.867296,0.001198132,0.1241287,0.001580676,0.0001397876,0.0001313191,0.001735178,0.0004786592,0.003311466],"genre_scores_gemma":[0.9835584,0.0003169005,0.01344802,0.0001233655,0.00006479482,0.00007420097,0.0008957488,0.00002789769,0.001490572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002824847,"threshold_uncertainty_score":0.00920099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03410875391028952,"score_gpt":0.4342590916583647,"score_spread":0.4001503377480752,"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."}}