{"id":"W6969248981","doi":"10.5683/sp3/mgqybr","title":"Data set of \"Smart\" Brace Validation Study","year":2023,"lang":"en","type":"dataset","venue":"Borealis","topic":"Logic, programming, and type systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Inertial measurement unit; Brace; Treadmill; Session (web analytics); Motion capture; Data set; Set (abstract data type)","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":[0.001218718,0.0002270614,0.0004023239,0.0001808514,0.00007674051,0.000214474,0.004135729,0.0001671133,0.000004932956],"category_scores_gemma":[0.0002057922,0.0001945733,0.00005539193,0.0004706309,0.0000350102,0.0003360801,0.00180089,0.0001804418,0.0002093357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002512978,"about_ca_system_score_gemma":0.0001348862,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.09380561,"about_ca_topic_score_gemma":0.0292921,"domain_scores_codex":[0.9976719,0.0002368369,0.000471655,0.0007312041,0.0006356252,0.0002527911],"domain_scores_gemma":[0.994962,0.0001350412,0.0004374096,0.004275083,0.0001167328,0.00007369681],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002577525,0.00009714712,0.00006149202,0.00009460458,0.00007165526,0.00004126789,0.0001400035,0.000001837938,3.141389e-7,0.0005960182,0.9971788,0.001714282],"study_design_scores_gemma":[0.000188542,0.0001981701,0.000365767,0.000009002027,0.00005469946,0.000005476381,0.00006995718,0.0001578436,0.000006720149,0.0004643064,0.9982783,0.0002012045],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000003987554,0.00005307052,0.004388886,0.00007370207,0.0007488349,0.0005838848,0.99388,0.0001557228,0.0001119302],"genre_scores_gemma":[0.0002822852,0.00003671553,0.0001426279,0.00002379739,0.0002706725,0.000033624,0.9990453,0.00001469849,0.0001503255],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0645135,"threshold_uncertainty_score":0.9884208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09349282764668586,"score_gpt":0.331080386219708,"score_spread":0.2375875585730221,"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."}}