{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002735356,0.002557229,0.001759682,0.00160338,0.001009854,0.001404625,0.003420805,0.003058184,0.01617786],"category_scores_gemma":[0.007787025,0.0004979818,0.00161796,0.001934619,0.0008086871,0.0009141441,0.001900683,0.001999541,0.03513648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009601127,"about_ca_system_score_gemma":0.001543396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01449259,"about_ca_topic_score_gemma":0.02545249,"domain_scores_codex":[0.9971679,0.000623467,0.0003105453,0.000677023,0.0009302664,0.0002908447],"domain_scores_gemma":[0.9956172,0.0008093888,0.0002762345,0.001262669,0.001773146,0.0002613984],"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":[0.001112247,0.0008094974,0.01285663,0.001594563,0.0002070675,0.0003013565,0.0001179898,0.00332577,0.0014947,0.0006450329,0.9410731,0.03646199],"study_design_scores_gemma":[0.001342486,0.0008507748,0.08239236,0.0009051396,0.0002190508,0.0009214922,0.0006142801,0.01019817,0.006400759,0.001888095,0.8939864,0.0002809885],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01862996,0.0008357437,0.002245761,0.0003502771,0.0004419564,0.0004113949,0.9698575,0.001766196,0.005461254],"genre_scores_gemma":[0.01426368,0.0001292884,0.002040171,0.0001877287,0.00004205378,0.0007435828,0.979215,0.0001545017,0.003224068],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01617786,"threshold_uncertainty_score":0.05412036,"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."}}