{"id":"W7133311426","doi":"10.1109/ijcb65343.2025.11411353","title":"First International StepUP Competition for Biometric Footstep Recognition: Methods, Results and Remaining Challenges","year":2025,"lang":"","type":"article","venue":"","topic":"Gait Recognition and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; Atlantic Canada Opportunities Agency; New Brunswick Innovation Foundation","keywords":"Biometrics; Robustness (evolution); Competition (biology); Competitor analysis; Set (abstract data type); Field (mathematics)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01454098,0.005426284,0.004329493,0.002926003,0.001369355,0.004067407,0.004141653,0.004653001,0.01398874],"category_scores_gemma":[0.01545606,0.0006641729,0.002588701,0.001803983,0.001094633,0.003380959,0.004778572,0.003447835,0.02009401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001572864,"about_ca_system_score_gemma":0.003382293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0164849,"about_ca_topic_score_gemma":0.02168215,"domain_scores_codex":[0.9895924,0.002218844,0.0005639968,0.001922149,0.004673076,0.001029401],"domain_scores_gemma":[0.9876051,0.001789532,0.0001797807,0.002162803,0.006696555,0.001566172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001020243,0.0006480925,0.002149401,0.0007805118,0.0004341726,0.0002647073,0.00007005025,0.004759694,0.007661987,0.001733285,0.6405427,0.3399351],"study_design_scores_gemma":[0.0006124665,0.002322149,0.02683366,0.001180887,0.000653373,0.00214142,0.0007212824,0.1771529,0.04574149,0.0102942,0.7319191,0.0004270691],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1500699,0.07261925,0.3707728,0.0317779,0.07262057,0.004565078,0.1293234,0.07087906,0.09737208],"genre_scores_gemma":[0.1449498,0.01190674,0.2127817,0.006756303,0.004532244,0.002168828,0.4728799,0.005950025,0.1380745],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0164849,"threshold_uncertainty_score":0.0769009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06860898262779098,"score_gpt":0.331113060658154,"score_spread":0.262504078030363,"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."}}