{"id":"W3135542633","doi":"10.3390/s21051669","title":"Out-of-Distribution Detection of Human Activity Recognition with Smartwatch Inertial Sensors","year":2021,"lang":"en","type":"article","venue":"Sensors","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Workplace Safety and Insurance Board","keywords":"Smartwatch; Artificial intelligence; Machine learning; Deep learning; Activity recognition; Computer science; Context (archaeology); Inertial measurement unit; Wearable computer","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":[0.0003109245,0.000176756,0.0003494937,0.0001067573,0.0001114217,0.00004715393,0.0001577731,0.0001252067,0.0000184112],"category_scores_gemma":[0.0001378028,0.00017642,0.0001220237,0.0005919937,0.00008426713,0.0004158561,0.00008376701,0.000189046,0.00002791965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009072899,"about_ca_system_score_gemma":0.00009286522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003553204,"about_ca_topic_score_gemma":0.0008755717,"domain_scores_codex":[0.9981577,0.000390469,0.0003607915,0.0004432389,0.0004204688,0.000227281],"domain_scores_gemma":[0.9981443,0.0001670023,0.0003959073,0.0004823952,0.0007332455,0.00007716675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009691884,0.0002896015,0.001002362,0.0001069375,0.00009719175,0.00003713853,0.000920538,0.00007700785,0.8596665,0.00005830866,0.00003855922,0.1376089],"study_design_scores_gemma":[0.0006627521,0.0002651817,0.008270159,0.0001101878,0.00003074198,0.00007069288,0.0001879193,0.003431603,0.9863201,0.0001400652,0.0002778748,0.0002327581],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9379916,0.000009199782,0.06060051,0.000140117,0.0004350258,0.0001938584,0.00005316867,0.0001229555,0.0004535544],"genre_scores_gemma":[0.9992777,0.000003781718,0.0004267099,0.00001023376,0.00008792444,0.00001074384,0.00004374496,0.00001334056,0.0001258523],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1373761,"threshold_uncertainty_score":0.71942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03629879010880702,"score_gpt":0.2601673507669572,"score_spread":0.2238685606581502,"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."}}