{"id":"W4401416717","doi":"10.1123/jab.2024-0007","title":"Interlaboratory Study Toward Combining Gait Kinematics Data Sets of Long-Distance Runners","year":2024,"lang":"en","type":"article","venue":"Journal of Applied Biomechanics","topic":"Lower Extremity Biomechanics and Pathologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Sagittal plane; Kinematics; Transverse plane; Biomechanics; Gait; Ankle; Coronal plane; Orthodontics; Gait analysis; Standard deviation; Medicine; Physical medicine and rehabilitation; Mathematics; Physical therapy; Statistics; Anatomy; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009658845,0.0002440583,0.0004968395,0.0003915762,0.00002805165,0.0001066883,0.0009199627,0.0001309177,0.00006555372],"category_scores_gemma":[0.00003353555,0.0002073156,0.00008469914,0.0007537085,0.00002806858,0.0002058396,0.0002591803,0.000413185,0.00001268477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008522105,"about_ca_system_score_gemma":0.00008522233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001019699,"about_ca_topic_score_gemma":0.000004602868,"domain_scores_codex":[0.9982132,0.00001916288,0.0008516305,0.0002272945,0.0004448891,0.0002437636],"domain_scores_gemma":[0.9988737,0.000112603,0.0002308803,0.0005628993,0.0001256021,0.00009428643],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004280585,0.001581023,0.00004392762,0.007139454,0.003732179,0.002922963,0.01818459,0.002677219,0.6024547,0.01508025,0.0744217,0.2713339],"study_design_scores_gemma":[0.003432656,0.002319639,0.00006055679,0.002672796,0.00120994,0.000421339,0.02955728,0.7777464,0.139497,0.01751716,0.02344911,0.002116033],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6680576,0.006762846,0.3089757,0.0001834196,0.009872057,0.001146876,0.002544685,0.0007285806,0.001728256],"genre_scores_gemma":[0.9940934,0.0002960952,0.005384044,0.00002056733,0.00009535246,0.000003484041,0.00004684126,0.0000529298,0.000007356017],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7750692,"threshold_uncertainty_score":0.8454086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03841064390112252,"score_gpt":0.276232794009107,"score_spread":0.2378221501079845,"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."}}