{"id":"W4225249014","doi":"10.1016/j.cub.2022.03.076","title":"Running in the wild: Energetics explain ecological running speeds","year":2022,"lang":"en","type":"article","venue":"Current Biology","topic":"Sports Performance and Training","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"National Institute of Biomedical Imaging and Bioengineering","keywords":"Energetics; Biology; Ecology; Energy metabolism","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":[0.0006308044,0.0001115064,0.0002154347,0.0001390156,0.0001928076,0.000006016523,0.0001653796,0.00005176447,0.000462783],"category_scores_gemma":[0.00002296472,0.00007464727,0.00006199741,0.0002712997,0.00008728819,0.00002436725,0.0001179426,0.000606116,0.00001319395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005626541,"about_ca_system_score_gemma":0.00005785166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007292485,"about_ca_topic_score_gemma":0.000003399967,"domain_scores_codex":[0.9990484,0.00003487718,0.0002468014,0.0002146764,0.000118838,0.0003364521],"domain_scores_gemma":[0.9996594,0.00004764553,0.00006602396,0.000174868,0.00001255164,0.00003948442],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005907077,0.0002260091,0.9663622,0.00001242445,0.00001103177,0.00007604652,0.0018612,0.0001082226,0.0002032769,0.003500498,0.0008923615,0.02668767],"study_design_scores_gemma":[0.00158407,0.0008726259,0.5058472,0.00003378264,0.00003960738,0.0002579711,0.004294291,0.00139007,0.00005812103,0.0004050983,0.4850239,0.000193271],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949552,0.001354959,0.00001809678,0.0008284211,0.0009371993,0.0001577613,0.000002490953,0.00003555184,0.001710314],"genre_scores_gemma":[0.998094,0.0001285421,0.0001123341,0.001071974,0.0003274395,0.00007827581,0.0001416375,0.000008107001,0.00003764431],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4841316,"threshold_uncertainty_score":0.5067149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06194859341420145,"score_gpt":0.3446090870385328,"score_spread":0.2826604936243313,"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."}}