{"id":"W1586104854","doi":"10.1002/9780470549148.app1","title":"Appendix A: Kinematic, Kinetic, and Energy Data","year":2009,"lang":"en","type":"other","venue":"","topic":"Sports Performance and Training","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Kinematics; Ankle; Table (database); Physics; Geodesy; Geology; Anatomy; Medicine; Computer science; Classical mechanics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00150625,0.001409948,0.00139676,0.002119968,0.0007266609,0.001084576,0.001367921,0.001019952,0.7461748],"category_scores_gemma":[0.02181777,0.0006780335,0.0005978417,0.002717741,0.0002589118,0.001286946,0.0008905266,0.001050191,0.4006423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000813582,"about_ca_system_score_gemma":0.001698136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005802051,"about_ca_topic_score_gemma":0.006289786,"domain_scores_codex":[0.9990683,0.0001783579,0.0002204623,0.0001491674,0.0003458796,0.00003781706],"domain_scores_gemma":[0.9843406,0.00651059,0.0005115594,0.001519155,0.00675319,0.0003648795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002041159,0.0001120284,0.0005701543,0.0004448737,0.000009939741,0.00003218173,0.00002321412,0.0003145935,0.0001167399,0.0005324715,0.9678228,0.02981691],"study_design_scores_gemma":[0.0003561576,0.0003386886,0.01443817,0.0008218025,0.00002835862,0.0003231469,0.0001634764,0.001259357,0.00051686,0.007300074,0.9743784,0.00007552237],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001458007,0.0002939815,0.007954122,0.0004507283,0.000755053,0.001701547,0.9484307,0.002208711,0.03674712],"genre_scores_gemma":[0.01052004,0.0009695506,0.02136327,0.0007376413,0.0003869105,0.008450895,0.8701617,0.002035843,0.08537415],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7461748,"threshold_uncertainty_score":0.3620509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02984168002145882,"score_gpt":0.2859905184770801,"score_spread":0.2561488384556213,"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."}}