{"id":"W1981558234","doi":"10.2316/journal.206.2014.4.206-3984","title":"UPPER LIMB MOTOR REHABILITATION INTEGRATED WITH VIDEO GAMES FOCUSING ON TRAINING FINGERS’ FINE MOVEMENTS","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Physical medicine and rehabilitation; Rehabilitation; Movement (music); Upper limb; Robot; Computer science; Training (meteorology); Psychology; Medicine; Physical therapy; Artificial intelligence; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.000173113,0.0008905419,0.0004804907,0.0005477917,0.0001419431,0.0002883798,0.000500488,0.0003861543,0.004449837],"category_scores_gemma":[0.0002893594,0.0001312337,0.0005008049,0.000195497,0.0001774664,0.0002940082,0.0004696572,0.0003245311,0.0008304596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001367026,"about_ca_system_score_gemma":0.0003022481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001541753,"about_ca_topic_score_gemma":0.002154808,"domain_scores_codex":[0.9998696,0.00002063359,0.000009757033,0.00002677758,0.00003982401,0.0000333889],"domain_scores_gemma":[0.999944,0.0000146509,0.000006259873,0.000005036938,0.00001408815,0.00001590306],"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":[0.004777284,0.006079918,0.002765035,0.001687351,0.0003412791,0.0007044757,0.0001704178,0.005952924,0.2644692,0.001090692,0.004644876,0.7073165],"study_design_scores_gemma":[0.004765926,0.06640948,0.2212358,0.0008767944,0.002115924,0.009511351,0.0005130799,0.1535289,0.4705034,0.00408651,0.06605509,0.00039766],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7583992,0.006481434,0.2071808,0.0003244868,0.0005422896,0.002440527,0.001086874,0.004219344,0.01932501],"genre_scores_gemma":[0.927898,0.002186642,0.05449032,0.000270125,0.00008913283,0.0009393725,0.0006088533,0.00007589108,0.01344159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004449837,"threshold_uncertainty_score":0.0148862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01202060361050861,"score_gpt":0.268624357375322,"score_spread":0.2566037537648134,"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."}}