{"id":"W4285417645","doi":"10.2196/31305","title":"Lessons Learned From Clinicians and Stroke Survivors About Using Telerehabilitation Combined With Exergames: Multiple Case Study","year":2022,"lang":"en","type":"article","venue":"JMIR Rehabilitation and Assistive Technologies","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; McGill University; Université de Sherbrooke; Université de Montréal; Centre for Interdisciplinary Research in Rehabilitation","funders":"","keywords":"Telerehabilitation; Stroke (engine); Physical medicine and rehabilitation; Physical therapy; Psychology; Medicine; Telemedicine; Engineering; Health care; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002448357,0.0009640404,0.0008608862,0.001204274,0.009579439,0.002437217,0.001817793,0.00454224,0.003749556],"category_scores_gemma":[0.01004896,0.0009018952,0.0007603482,0.001666422,0.002139057,0.002530962,0.002859245,0.003307838,0.0006284404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003876919,"about_ca_system_score_gemma":0.003439261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01003502,"about_ca_topic_score_gemma":0.03926166,"domain_scores_codex":[0.9960936,0.001969671,0.000281875,0.0004202237,0.0004761631,0.0007585171],"domain_scores_gemma":[0.9963813,0.00161382,0.0007111897,0.0001344873,0.0003384707,0.0008206539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001756764,0.002627932,0.05961708,0.0006842299,0.00007398603,0.4103646,0.4694666,0.0002827867,0.001363541,0.001817954,0.007939633,0.04558602],"study_design_scores_gemma":[0.0001040037,0.0008491927,0.02214241,0.001029177,0.00007678576,0.3134932,0.6255834,0.0006970481,0.00117835,0.001498157,0.03321109,0.0001372128],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9813104,0.00253058,0.001235417,0.00636684,0.0001244599,0.0003448149,0.00006291415,0.00002701822,0.007997486],"genre_scores_gemma":[0.9856287,0.004172461,0.002578926,0.002396324,0.000165304,0.0003904182,0.00006898438,0.00003086026,0.004568072],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01003502,"threshold_uncertainty_score":0.02812916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04730384181181822,"score_gpt":0.3460955362824514,"score_spread":0.2987916944706332,"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."}}