{"id":"W4394441474","doi":"10.6084/m9.figshare.20337302","title":"KINEMATIC ANALYSIS OF LOWER EXTREMITY MOVEMENT TECHNIQUES IN SOCCER TRAINING","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Sports Performance and Training","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; University Health Network; Canadian Institute for Advanced Research; University of Toronto","funders":"","keywords":"Kinematics; Movement (music); Physical medicine and rehabilitation; Training (meteorology); Computer science; Aeronautics; Medicine; Geography; Engineering; Meteorology; Physics; Acoustics","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":[0.002457665,0.002337767,0.002592085,0.004185006,0.0006490945,0.001992789,0.003587052,0.001853683,0.07943016],"category_scores_gemma":[0.01848481,0.0005732119,0.003436505,0.004887026,0.0004490671,0.0009524381,0.002424037,0.001482297,0.02692139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009465259,"about_ca_system_score_gemma":0.002304167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01043744,"about_ca_topic_score_gemma":0.02035335,"domain_scores_codex":[0.9976636,0.0005217969,0.0005939844,0.0006330504,0.000389201,0.00019831],"domain_scores_gemma":[0.9926113,0.002984286,0.001467609,0.001108504,0.001537125,0.0002911637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.002618043,0.0003201873,0.02297697,0.03897412,0.001913007,0.0001101288,0.00008690082,0.001710962,0.0003322185,0.0006238035,0.8887022,0.0416315],"study_design_scores_gemma":[0.007864811,0.0005459285,0.1742641,0.01691819,0.00374713,0.0005594408,0.0003022293,0.003873951,0.00145846,0.0038541,0.7862964,0.0003152526],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001111688,0.0009362859,0.0002139605,0.0001063846,0.00005921105,0.000147296,0.996613,0.0002514257,0.000560822],"genre_scores_gemma":[0.005742811,0.0006296477,0.00108415,0.0001072236,0.00004298985,0.001650074,0.9894567,0.00007930046,0.001207095],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07943016,"threshold_uncertainty_score":0.2657204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06935827727861572,"score_gpt":0.3284246251824574,"score_spread":0.2590663479038416,"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."}}