{"id":"W4397033587","doi":"10.1007/s00421-024-05504-4","title":"Identifying physiological determinants of 800 m running performance using post-exercise blood lactate kinetics","year":2024,"lang":"en","type":"article","venue":"European Journal of Applied Physiology","topic":"Sports Performance and Training","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Japan Society for the Promotion of Science; University of Tokyo","keywords":"Blood lactate; Human physiology; Sports medicine; Kinetics; Medicine; Physical therapy; Chemistry; Internal medicine; Heart rate; Blood pressure; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005844833,0.0005682643,0.0003713302,0.000382568,0.0001023541,0.000643233,0.0001758098,0.0004142569,0.0008451512],"category_scores_gemma":[0.001404156,0.0001597703,0.0001659095,0.0002925491,0.0001172641,0.0003327676,0.0001976481,0.0001932231,0.0003044458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008273099,"about_ca_system_score_gemma":0.0001643136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001688027,"about_ca_topic_score_gemma":0.0015408,"domain_scores_codex":[0.9998114,0.00005464956,0.00001496126,0.00005826488,0.00003339249,0.00002742732],"domain_scores_gemma":[0.999388,0.0002092272,0.0002054339,0.00003419957,0.0001002521,0.00006295814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00119088,0.0002918968,0.9239694,0.00009081647,0.0001681767,0.0001117604,0.0001238421,0.001567159,0.04773563,0.00005298617,0.000117015,0.02458046],"study_design_scores_gemma":[0.0000070567,0.0003383647,0.9938699,0.000008996088,0.0000387359,0.00007692821,0.00006792822,0.002697123,0.002738376,0.00004541774,0.0001042883,0.000007003782],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979073,0.0001494872,0.001547559,0.00001015001,0.000002821648,0.00001261153,0.0000790039,0.0000118466,0.0002791976],"genre_scores_gemma":[0.9986122,0.00006321062,0.0008470843,0.00001310735,0.000007352121,0.00001133696,0.0001558865,0.000004410021,0.000285516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001688027,"threshold_uncertainty_score":0.003356338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04491045689178551,"score_gpt":0.2943501437275892,"score_spread":0.2494396868358036,"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."}}