{"id":"W3199057864","doi":"10.1109/iaict52856.2021.9532513","title":"IoT device for Athlete's movements recognition using inertial measurement unit (IMU)","year":2021,"lang":"en","type":"article","venue":"","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"","keywords":"Inertial measurement unit; Wearable computer; Units of measurement; Computer science; Data collection; Visualization; Athletes; Protocol (science); Internet of Things; Real-time computing; Simulation; 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":[0.0001896187,0.0005004386,0.0004284984,0.0007129585,0.0002102985,0.0004274709,0.0004216905,0.0005568704,0.003189937],"category_scores_gemma":[0.0003906113,0.000180734,0.0002400288,0.0005219509,0.0001353428,0.0004474526,0.0004273564,0.0002177486,0.00143205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008441439,"about_ca_system_score_gemma":0.0001267745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002394078,"about_ca_topic_score_gemma":0.000458014,"domain_scores_codex":[0.9997209,0.00004496289,0.00002880904,0.00007400936,0.0001053764,0.00002595848],"domain_scores_gemma":[0.9998538,0.00003356515,0.00002977237,0.00002602649,0.00004166548,0.0000150477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007308752,0.0002807685,0.02219203,0.001088252,0.0001411032,0.0009405836,0.0004453687,0.001882909,0.3568998,0.00285817,0.01148377,0.6010563],"study_design_scores_gemma":[0.0001901117,0.004081305,0.1846462,0.00102333,0.0008511951,0.009171841,0.0009988871,0.1096823,0.4885205,0.004707197,0.1958174,0.0003098434],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2934194,0.005731774,0.6497467,0.0005349261,0.001041068,0.0006885527,0.002292678,0.007807636,0.03873739],"genre_scores_gemma":[0.8592594,0.002069693,0.119488,0.0004849528,0.0002908855,0.0005691334,0.001254592,0.0001028583,0.01648052],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003189937,"threshold_uncertainty_score":0.01067144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.249847642189155,"score_gpt":0.3195045913151134,"score_spread":0.06965694912595849,"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."}}