{"id":"W4402841686","doi":"10.1088/1361-6501/ad7f78","title":"Simple and efficient step detection algorithm for foot-mounted IMU","year":2024,"lang":"en","type":"article","venue":"Measurement Science and Technology","topic":"Mechanical Engineering and Vibrations Research","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Simple (philosophy); Inertial measurement unit; Computer science; Foot (prosody); Algorithm; SIMPLE algorithm; Step detection; Artificial intelligence; Computer vision; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009132329,0.00007061499,0.0000712332,0.000422862,0.0001432533,0.00008510934,0.00009015302,0.00006112316,0.000002629721],"category_scores_gemma":[0.0001844339,0.00006150699,0.000009372928,0.000876201,0.0001262491,0.00005856654,0.00003487201,0.0001110329,0.000003090066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001182593,"about_ca_system_score_gemma":0.00003972855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003349305,"about_ca_topic_score_gemma":0.0000075526,"domain_scores_codex":[0.9991025,0.000002900422,0.00009151146,0.0002091226,0.0003586948,0.0002352397],"domain_scores_gemma":[0.9996335,0.00001752479,0.000003838676,0.0001059439,0.000187069,0.00005213677],"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":[7.161211e-7,0.000006327127,0.000001737744,0.00006194389,0.000008891053,8.982794e-7,0.00001088141,0.0006289711,0.2856504,0.002815976,0.00007054535,0.7107427],"study_design_scores_gemma":[0.00008796567,0.00008014425,0.00001506372,0.00001711245,0.000004552394,0.000006555871,0.00003840644,0.8905742,0.1016794,0.0004393779,0.006992357,0.00006488157],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03575136,0.001283308,0.9615791,0.000199291,0.0002138073,0.0002548545,0.000003975446,0.000605938,0.0001084026],"genre_scores_gemma":[0.9974581,0.00003710954,0.002385596,0.000003328137,0.00001893456,0.00008026166,3.598543e-7,0.000008709341,0.000007616854],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9617067,"threshold_uncertainty_score":0.2508182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02076875237379447,"score_gpt":0.268427690421687,"score_spread":0.2476589380478925,"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."}}