{"id":"W3168864574","doi":"10.2196/30233","title":"Technologies to Support Assessment of Movement During Video Consultations: Exploratory Study","year":2021,"lang":"en","type":"article","venue":"JMIRx Med","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Regional Development Fund; Medical Research Council; National Institute for Health and Care Research; UK Research and Innovation","keywords":"Movement assessment; Movement (music); Computer science; Test (biology); Mobile phone; Multimedia; Rehabilitation; Phone; Tracking (education); Physical medicine and rehabilitation; Match moving; Motion (physics); Medicine; Physical therapy; Psychology; Artificial intelligence","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":[0.010021,0.0007929258,0.0005315236,0.001995146,0.0009673001,0.00127155,0.0008772221,0.00125105,0.002200355],"category_scores_gemma":[0.03128684,0.0005354783,0.0008936942,0.000955486,0.0008448521,0.001518064,0.001264046,0.0007687408,0.0004756294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001116075,"about_ca_system_score_gemma":0.001907823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001348367,"about_ca_topic_score_gemma":0.002477192,"domain_scores_codex":[0.9901733,0.006887343,0.0007285079,0.0004162834,0.001064931,0.0007296001],"domain_scores_gemma":[0.9645311,0.02693586,0.002857816,0.001004468,0.003738325,0.0009323247],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01052598,0.08945134,0.3159053,0.01565493,0.0008298316,0.007813745,0.1170566,0.002467206,0.0174289,0.001760286,0.002995404,0.4181105],"study_design_scores_gemma":[0.00398689,0.3040277,0.4379031,0.005456219,0.00212452,0.009335648,0.1687734,0.008001494,0.02900696,0.001417969,0.02944954,0.0005166034],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919172,0.0004264199,0.002026221,0.00007636331,0.00001225877,0.003481433,0.0001557855,0.0000200204,0.001884285],"genre_scores_gemma":[0.98049,0.0009754901,0.01249346,0.0002435318,0.0000332351,0.004855362,0.0001498587,0.000015382,0.000743764],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.010021,"threshold_uncertainty_score":0.05299675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02609413212935824,"score_gpt":0.3524254247167086,"score_spread":0.3263312925873503,"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."}}