{"id":"W4416524583","doi":"10.1016/j.eij.2025.100805","title":"Continuous Well-Being assessment and actionable feedback using explainable regression for Edge-Enabled wearable devices","year":2025,"lang":"en","type":"article","venue":"Egyptian Informatics Journal","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"","keywords":"Interpretability; Wearable computer; Wearable technology; Counterfactual thinking; Regression; Mean squared error; Decision support system; Range (aeronautics)","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001544849,0.0002393426,0.0004130069,0.0004784803,0.001247695,0.001956708,0.0005115762,0.0001254768,0.00003506323],"category_scores_gemma":[0.0000789932,0.000212233,0.0001148446,0.0004384588,0.00004083378,0.004097298,0.0002671778,0.0004154671,0.00001662036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003577769,"about_ca_system_score_gemma":0.0005222703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000205432,"about_ca_topic_score_gemma":0.000008327924,"domain_scores_codex":[0.9979448,0.0001057905,0.000863037,0.0001911424,0.0003842456,0.0005110108],"domain_scores_gemma":[0.9979163,0.0003491947,0.0006877151,0.0003365235,0.0005297057,0.0001804905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005619427,0.00101737,0.03054003,0.006734704,0.002124878,0.0001477469,0.04096383,0.009272859,0.006045953,0.03856355,0.084525,0.7795022],"study_design_scores_gemma":[0.004577363,0.0003140948,0.001757674,0.003713034,0.0001102612,0.001420329,0.0120855,0.8304173,0.003371802,0.009162702,0.1322411,0.0008288543],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08582938,0.0002655122,0.8868362,0.0006253944,0.001479436,0.0005691081,0.000002224617,0.0001018365,0.02429095],"genre_scores_gemma":[0.7900618,0.0001288453,0.2046141,0.0007939533,0.0002472755,0.00005073217,0.000003954412,0.00002255069,0.004076788],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8211444,"threshold_uncertainty_score":0.9990793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01987196475374084,"score_gpt":0.3045013754062764,"score_spread":0.2846294106525356,"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."}}