{"id":"W4407126022","doi":"10.1186/s12984-025-01554-7","title":"PhantomAR: gamified mixed reality system for alleviating phantom limb pain in upper limb amputees—design, implementation, and clinical usability evaluation","year":2025,"lang":"en","type":"article","venue":"Journal of NeuroEngineering and Rehabilitation","topic":"Pain Management and Treatment","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medizinischen Fakultät, Eberhard Karls Universität Tübingen; Japan Society for the Promotion of Science; Eberhard Karls Universität Tübingen","keywords":"Usability; Wearable computer; Physical medicine and rehabilitation; Phantom limb; Virtual reality; Likert scale; Amputation; Computer science; Augmented reality; Human–computer interaction; Physical therapy; Quality of life (healthcare); Phantom limb pain; Activities of daily living; Occupational therapy; Psychology; Medicine; Nursing","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":[0.002277859,0.0009339596,0.0005969111,0.0007398334,0.0001874536,0.0008074155,0.001022415,0.000602444,0.002747053],"category_scores_gemma":[0.003234418,0.0003881603,0.0005151044,0.0002174926,0.0004121057,0.000537943,0.0009450885,0.0003886051,0.000449423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002287855,"about_ca_system_score_gemma":0.000454658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000585483,"about_ca_topic_score_gemma":0.0007094435,"domain_scores_codex":[0.9991282,0.0004172426,0.00007016509,0.00009893824,0.0002137639,0.00007169801],"domain_scores_gemma":[0.9991018,0.000463541,0.00006213818,0.00006415273,0.0002013648,0.000106968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01023581,0.01311478,0.01798256,0.004857504,0.0006510981,0.003062066,0.005317073,0.01143365,0.2783286,0.00174655,0.006999927,0.6462704],"study_design_scores_gemma":[0.00918883,0.1939662,0.2124612,0.001975134,0.003613867,0.01997164,0.005734248,0.2374707,0.2448936,0.001947499,0.06754278,0.001234285],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9144201,0.001099124,0.07575994,0.0002426337,0.0000775203,0.0035832,0.0004097952,0.002217345,0.002190347],"genre_scores_gemma":[0.861896,0.001137933,0.1290244,0.0002724567,0.00002700127,0.004170393,0.0004749074,0.0002019373,0.002794863],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002747053,"threshold_uncertainty_score":0.01204664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03479280235914566,"score_gpt":0.3757034449194085,"score_spread":0.3409106425602628,"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."}}