{"id":"W4376274585","doi":"10.20338/bjmb.v17i1.294","title":"The influence of athletic background, lower limb dominance and cutting angle on the center of mass kinematics during a sidestep cutting task","year":2023,"lang":"en","type":"article","venue":"Brazilian Journal of Motor Behavior","topic":"Sports injuries and prevention","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Kinematics; Trunk; Athletes; Angular acceleration; Physical medicine and rehabilitation; Trajectory; Simulation; Angular velocity; Psychology; Physical therapy; Medicine; Computer science; 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":[0.0008822091,0.0001277888,0.0003128425,0.00009835637,0.0001446572,0.00002564753,0.0001641135,0.00005429246,0.00002860084],"category_scores_gemma":[0.0002713698,0.00007510051,0.0001798113,0.0002015777,0.0001676928,0.0000985597,0.00004781205,0.0002626575,0.000002728909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003073857,"about_ca_system_score_gemma":0.00004087166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005001494,"about_ca_topic_score_gemma":0.000001650096,"domain_scores_codex":[0.9984478,0.00006022653,0.0007814624,0.0001093203,0.0003967666,0.0002044217],"domain_scores_gemma":[0.9983455,0.0002588146,0.0008320126,0.0002715304,0.0002203546,0.00007178474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002491249,0.0006185863,0.5044043,0.001020137,0.0001986346,0.0006523446,0.002184904,0.0001534834,0.4669294,0.0002504555,0.0004055966,0.02069085],"study_design_scores_gemma":[0.001218735,0.0009796057,0.9849151,0.002375174,0.0002385864,0.0002662152,0.001477718,0.00003639051,0.007884128,0.00005418856,0.0004609339,0.00009321329],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987173,0.0001784914,0.000007959884,0.0004915017,0.0002039338,0.0003314895,0.000009605499,0.000007134673,0.00005259704],"genre_scores_gemma":[0.9987879,0.000170314,0.0005019595,0.00004063354,0.0001045804,0.000008676752,8.504376e-7,0.00002073497,0.0003643899],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4805108,"threshold_uncertainty_score":0.306251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01428262208594981,"score_gpt":0.2786646119644179,"score_spread":0.2643819898784681,"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."}}