{"id":"W4416874399","doi":"10.1109/icoici65217.2025.11252631","title":"Deep Learning-based Temporal-Spatial Model for Stroke Rehabilitation Posture Estimation using StrokePoseNet","year":2025,"lang":"","type":"article","venue":"","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Rehabilitation; Stroke (engine); Convolutional neural network; Deep learning; Artificial neural network","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":[0.0002614118,0.0009032643,0.0005010699,0.0004445748,0.0001646481,0.00039058,0.0007399592,0.000563421,0.001830278],"category_scores_gemma":[0.0006000343,0.0002925957,0.0005746271,0.0003854386,0.0001591512,0.0004414766,0.0004344507,0.000781975,0.0006591245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006209757,"about_ca_system_score_gemma":0.0008755574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01623172,"about_ca_topic_score_gemma":0.0247124,"domain_scores_codex":[0.9998909,0.00001131514,0.00000750134,0.00004341412,0.00002228582,0.00002449338],"domain_scores_gemma":[0.9999052,0.00002453349,0.00001179448,0.000009330487,0.00003980026,0.000009242633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003765294,0.0003107748,0.007867633,0.0001183602,0.0001741977,0.0002230165,0.00004808099,0.5519595,0.0124118,0.001441884,0.008302866,0.4167654],"study_design_scores_gemma":[0.000004163819,0.0000428664,0.0009073506,0.000008474061,0.00001417769,0.00002324328,0.000005614714,0.9964173,0.001593355,0.0004903889,0.0004875397,0.000005584105],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2373068,0.002634357,0.7433122,0.0007268288,0.0005036094,0.000167386,0.003318381,0.006479007,0.00555136],"genre_scores_gemma":[0.9254123,0.0007025874,0.06155873,0.0003407153,0.0000727332,0.0001915514,0.003825817,0.0000803526,0.007815273],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01623172,"threshold_uncertainty_score":0.03227448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01426219644030483,"score_gpt":0.3090779655116195,"score_spread":0.2948157690713147,"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."}}