{"id":"W2279611297","doi":"10.1123/jab.2015-0125","title":"Can Trained Runners Effectively Attenuate Impact Acceleration During Repeated High-Intensity Running Bouts?","year":2015,"lang":"en","type":"article","venue":"Journal of Applied Biomechanics","topic":"Lower Extremity Biomechanics and Pathologies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Indiana University Bloomington","keywords":"STRIDE; Treadmill; Rating of perceived exertion; Intensity (physics); Physical medicine and rehabilitation; Acceleration; Blood lactate; Medicine; Physical therapy; Attenuation; Simulation; Heart rate; Computer science; Physics; Internal medicine; Blood pressure","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":[0.0002836309,0.000329245,0.0003834179,0.00009602693,0.0001125074,0.0002717312,0.0002693176,0.0006241326,0.001677122],"category_scores_gemma":[0.000801323,0.0001051336,0.0001966906,0.00005816256,0.0001804802,0.0002761542,0.0001711293,0.000322399,0.0004659684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005215032,"about_ca_system_score_gemma":0.000161132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007290794,"about_ca_topic_score_gemma":0.001483414,"domain_scores_codex":[0.9999223,0.00002209603,0.000005887959,0.00001724485,0.00001035823,0.00002222264],"domain_scores_gemma":[0.9998026,0.00004008674,0.00004339025,0.00002043981,0.00003103038,0.00006243478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.01281548,0.01193278,0.09910533,0.001923989,0.0006425537,0.001030772,0.0009808403,0.00174297,0.5690808,0.0001894347,0.0009354491,0.2996195],"study_design_scores_gemma":[0.0005183216,0.06012599,0.891693,0.0002563154,0.0006267775,0.000974977,0.00133448,0.0031029,0.03721795,0.0004670788,0.003624593,0.00005763574],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998345,0.0007368199,0.0004173495,0.0001087588,0.00003397818,0.00002014742,0.00002227107,0.00001522388,0.000300386],"genre_scores_gemma":[0.9960673,0.001114368,0.0009399109,0.0001060642,0.00006508458,0.00004834088,0.0001053918,0.000005731921,0.00154782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001677122,"threshold_uncertainty_score":0.005610526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01865487217439857,"score_gpt":0.2255665048677672,"score_spread":0.2069116326933686,"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."}}