{"id":"W4400114404","doi":"10.1109/i2mtc60896.2024.10560997","title":"Hierarchical Classifier for Improved Human Activity Recognition using Wearable Sensors","year":2024,"lang":"en","type":"article","venue":"","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wearable computer; Activity recognition; Computer science; Classifier (UML); Artificial intelligence; Pattern recognition (psychology); Wearable technology; Embedded system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005827697,0.0006863644,0.0007651672,0.001358983,0.0002450527,0.0003721031,0.00065498,0.0003861554,0.001483237],"category_scores_gemma":[0.001351551,0.0001942521,0.0006985381,0.001330847,0.0001013812,0.0006756081,0.0004982976,0.0005651776,0.0009184889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003237206,"about_ca_system_score_gemma":0.0005672192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007594961,"about_ca_topic_score_gemma":0.008429721,"domain_scores_codex":[0.9994841,0.00008522249,0.00003683881,0.0001537041,0.0001673623,0.00007281316],"domain_scores_gemma":[0.9995872,0.0001132722,0.00004315264,0.00006071805,0.0001698548,0.00002580948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002614228,0.0002801169,0.0075331,0.0001237346,0.0001567799,0.000100628,0.00008485077,0.05251059,0.0181419,0.001208932,0.008404618,0.9111933],"study_design_scores_gemma":[0.00001560041,0.0001307059,0.00796373,0.00002017817,0.00005499343,0.00008264738,0.00004035995,0.9808466,0.006704406,0.001495348,0.002626268,0.00001912821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07918049,0.001506413,0.9104229,0.0001724278,0.0002525701,0.0001437137,0.001302783,0.004179721,0.002838984],"genre_scores_gemma":[0.7485337,0.0007506069,0.243175,0.0001587186,0.0001510321,0.0002160153,0.002986114,0.00008414592,0.003944658],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007594961,"threshold_uncertainty_score":0.01510155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1038448269874232,"score_gpt":0.329106358717736,"score_spread":0.2252615317303128,"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."}}