{"id":"W4406775175","doi":"10.3389/fcomp.2025.1514933","title":"WIMUSim: simulating realistic variabilities in wearable IMUs for human activity recognition","year":2025,"lang":"en","type":"article","venue":"Frontiers in Computer Science","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Horizon 2020 Framework Programme","keywords":"Wearable computer; Computer science; Human–computer interaction; Artificial intelligence; Embedded system","routes":{"ca_aff":true,"ca_fund":false,"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":[0.000374231,0.0007273063,0.000392792,0.0003695243,0.0002142985,0.0006395885,0.001000519,0.0007511764,0.002472019],"category_scores_gemma":[0.001913664,0.0003257419,0.0008010929,0.0002891264,0.0003530325,0.0004998813,0.0008063241,0.0004590768,0.0004852041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003015015,"about_ca_system_score_gemma":0.0004621692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004667384,"about_ca_topic_score_gemma":0.003763424,"domain_scores_codex":[0.9998474,0.00004706663,0.0000129868,0.00003216225,0.00004097835,0.00001936731],"domain_scores_gemma":[0.9996709,0.0001715662,0.00003652539,0.00005068954,0.00003998444,0.00003039223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001191929,0.00005928742,0.002870885,0.0001299394,0.00005011468,0.0001024797,0.0001075914,0.9707568,0.004067861,0.001749088,0.001166395,0.01882041],"study_design_scores_gemma":[0.00001606983,0.00006799091,0.0007105745,0.00001692336,0.000009626568,0.00003184619,0.00002082887,0.9948384,0.001998867,0.0007221652,0.001557415,0.000009343933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2659041,0.000520146,0.7195271,0.0003777134,0.0001825674,0.0003420006,0.001935801,0.004584802,0.00662573],"genre_scores_gemma":[0.9128835,0.0003177683,0.08279616,0.0001163199,0.00003184807,0.000421157,0.001258389,0.000239438,0.001935476],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004667384,"threshold_uncertainty_score":0.009280384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03139511520530828,"score_gpt":0.2946025816035224,"score_spread":0.2632074663982141,"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."}}