{"id":"W4382682424","doi":"10.1080/19424280.2023.2199288","title":"Technological advances in track spike design facilitate enhanced running performance","year":2023,"lang":"en","type":"article","venue":"Footwear Science","topic":"Lower Extremity Biomechanics and Pathologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Spike (software development); Track (disk drive); Computer science; Simulation; Data science; Software engineering; Operating system","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":[0.0010029,0.0005948084,0.0004081151,0.0008414797,0.0004315926,0.001619194,0.001332259,0.000956488,0.01087646],"category_scores_gemma":[0.001574717,0.0002592591,0.0005366179,0.000551274,0.0002279983,0.0008441854,0.0008685101,0.0007963072,0.004878894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003609853,"about_ca_system_score_gemma":0.0008965122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001245041,"about_ca_topic_score_gemma":0.004185705,"domain_scores_codex":[0.9993454,0.00007105366,0.00003708436,0.00007320924,0.0004064778,0.00006687413],"domain_scores_gemma":[0.9992931,0.000108806,0.0001094728,0.00006177132,0.0003639098,0.00006286973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006238747,0.00105243,0.01021561,0.001087079,0.0001066436,0.0003426734,0.0002359249,0.01751729,0.2355457,0.01196118,0.02421859,0.697093],"study_design_scores_gemma":[0.0005656029,0.008491676,0.04033153,0.0004731168,0.0004315339,0.002622922,0.0004766743,0.1666631,0.2162551,0.01420454,0.5491569,0.0003273436],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1675297,0.007629541,0.7367121,0.004427113,0.004720603,0.0005320954,0.001309829,0.004062101,0.07307693],"genre_scores_gemma":[0.6866784,0.004302887,0.259259,0.002140741,0.0008787026,0.0003605572,0.001581496,0.000857809,0.04394043],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01087646,"threshold_uncertainty_score":0.03638536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0396714750904139,"score_gpt":0.2450490176622947,"score_spread":0.2053775425718808,"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."}}