{"id":"W2297086838","doi":"10.1186/s12984-016-0114-0","title":"Evaluation of a smartphone human activity recognition application with able-bodied and stroke participants","year":2016,"lang":"en","type":"article","venue":"Journal of NeuroEngineering and Rehabilitation","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Ottawa Hospital Research Institute; University of Ottawa","keywords":"Wearable computer; Activity recognition; Population; Physical medicine and rehabilitation; Accelerometer; Medicine; Decision tree; Classifier (UML); Artificial intelligence; Computer science; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001392782,0.00008612851,0.0001832149,0.0002078575,0.00004320037,0.00002979052,0.00006552062,0.0000299965,0.000001219543],"category_scores_gemma":[0.0003900218,0.00005979527,0.00003265268,0.000133529,0.00004446741,0.0007115415,0.00001902784,0.00006961248,5.952061e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005302756,"about_ca_system_score_gemma":0.00004217379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001516118,"about_ca_topic_score_gemma":0.00001411533,"domain_scores_codex":[0.998791,0.0002056426,0.0003009195,0.0001582589,0.0004419677,0.0001022269],"domain_scores_gemma":[0.9982149,0.0005244233,0.0003623507,0.0001349567,0.0006946037,0.00006873548],"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":[0.00006566749,0.00009080335,0.003414564,0.00008246354,0.00004121293,9.208072e-7,0.0007469591,0.0002043701,0.3884812,0.00003985368,0.000007284147,0.6068247],"study_design_scores_gemma":[0.007606399,0.004898693,0.8440712,0.001297863,0.0003314271,0.0002525262,0.0002652792,0.09623773,0.04183843,0.002629101,0.0001372047,0.0004341502],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7786069,0.0000372966,0.2206566,0.0004336987,0.00006410094,0.0001670344,0.000002096501,0.00001535931,0.00001694613],"genre_scores_gemma":[0.9976237,0.00001496055,0.002294177,0.000003818485,0.0000319753,0.00001930616,2.465648e-7,0.000006530078,0.000005252783],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8406566,"threshold_uncertainty_score":0.243838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03756973449865986,"score_gpt":0.2743295337994425,"score_spread":0.2367597993007826,"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."}}