{"id":"W6950768869","doi":"10.5683/sp3/v6c59o","title":"GaitMotion: A Multitask Dataset for Pathological Gait Forecasting","year":2023,"lang":"en","type":"dataset","venue":"Borealis","topic":"Geochemistry and Elemental Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Gait; Gait analysis; Inertial measurement unit; Sample (material); Baseline (sea); Task (project management)","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":[0.0004433,0.003714123,0.001279774,0.002328021,0.0006521011,0.0009194555,0.002413269,0.002536036,0.01155895],"category_scores_gemma":[0.002026503,0.0004380051,0.001630349,0.002086239,0.000379403,0.0007084919,0.001613379,0.001235714,0.02158311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007539371,"about_ca_system_score_gemma":0.0009480006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02031819,"about_ca_topic_score_gemma":0.05365786,"domain_scores_codex":[0.9994305,0.00006586569,0.00006655914,0.0001752229,0.000156422,0.0001054114],"domain_scores_gemma":[0.9994884,0.00006368844,0.00005606636,0.0001485586,0.000152315,0.00009095037],"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":[0.0005583856,0.0003111793,0.007410234,0.0009429909,0.0001781499,0.000367582,0.00005216003,0.002673237,0.001836349,0.000425077,0.9439939,0.04125073],"study_design_scores_gemma":[0.001174246,0.0006756592,0.1009423,0.001146879,0.0004136817,0.002622522,0.0005727944,0.0501917,0.008753522,0.006204016,0.8268627,0.0004399698],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.008896572,0.0006373802,0.001911896,0.0001962691,0.0002712109,0.0001368537,0.9821863,0.004068603,0.001694855],"genre_scores_gemma":[0.006277188,0.0001283263,0.002010483,0.00006076798,0.00002557409,0.0001424506,0.9902924,0.00008754196,0.0009754339],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02031819,"threshold_uncertainty_score":0.04039985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06170187805656093,"score_gpt":0.2655054445417421,"score_spread":0.2038035664851812,"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."}}